Search

Your search keyword '"Balani, A."' showing total 3,351 results
Start Over Author "Balani, A."
3,351 results on '"Balani, A."'

6. Gemini: A Family of Highly Capable Multimodal Models

Author

Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.

Published
2023

9. Performance of Vasopressin Stimulated Bilateral Inferior Petrosal Sinus Sampling in Corticotropin Dependent Cushing’s Syndrome with Negative or Equivocal 3 Tesla Contrast Enhanced Magnetic Resonance Imaging of Pituitary

Author

Puneet Shivnani, Rajeev Kasliwal, Gourav Goyal, Jyoti Sharma, Utkarsh Balani, Pankaj Gupta, Bhawani S. Sharma, Dinesh Yadav, Vineet Mishra, and Surendra K. Sharma

Subjects
bipss – bilateral inferior petrosal sinus sampling, cd – cushing’s disease, cs – cushing’s syndrome, eas – ectopic acth secretion, lvp – lysine vasopressin, Diseases of the endocrine glands. Clinical endocrinology, RC648-665, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Introduction: Corticotropin releasing hormone (CRH)-stimulated bilateral inferior petrosal sinus sampling (BIPSS) is the most accurate procedure in the differential diagnosis of adrenocorticotropic hormone (ACTH)-dependent Cushing’s syndrome (CS) with a sensitivity of 88–100% and a specificity of 67–100%. However, CRH is not available globally currently. We undertook this study of BIPSS using lysine vasopressin (LVP) as an agent to stimulate the release of ACTH from corticotrophs. Our objective was to assess the accuracy of LVP-stimulated BIPSS in differentiating Cushing’s disease (CD) from ectopic ACTH syndrome (EAS) with negative or equivocal 3T contrast-enhanced MRI (CEMRI). Methods: Seventeen patients with clinically and biochemically confirmed ACTH-dependent CS with equivocal or negative CEMRI pituitary underwent BIPSS using LVP as a stimulating agent. Results: Of seventeen patients who underwent BIPSS, nine patients had a raised central-to-peripheral ACTH ratio and were classified as having CD that was confirmed on histopathology following transsphenoidal sinus surgery. Remaining eight patients, who did not show a raised central-to-peripheral ACTH ratio, were classified to have EAS. All patients with EAS underwent contrast-enhanced computerised tomography of the neck, chest, and abdomen and/or Gallium 68 DOTANOC positron emission tomography/computerised tomography. Seven out of eight patients demonstrated solitary pulmonary nodule in the lung (bronchial carcinoid), and one patient had a mass in the thymus (thymic carcinoid). Conclusion: BIPSS using LVP confirmed the source of ACTH excess correctly in all the patients with ACTH-dependent CS without the loss of specificity.

Published
2024
Full Text
View/download PDF

10. Online Two-stage Thermal History Prediction Method for Metal Additive Manufacturing of Thin Walls

Author

Tang, Yifan, Dehaghani, M. Rahmani, Sajadi, Pouyan, Balani, Shahriar Bakrani, Dhalpe, Akshay, Panicker, Suraj, Wu, Di, Coatanea, Eric, and Wang, G. Gary

Subjects
Computer Science - Machine Learning
Abstract

This paper aims to propose an online two-stage thermal history prediction method, which could be integrated into a metal AM process for performance control. Based on the similarity of temperature curves (curve segments of a temperature profile of one point) between any two successive layers, the first stage of the proposed method designs a layer-to-layer prediction model to estimate the temperature curves of the yet-to-print layer from measured temperatures of certain points on the previously printed layer. With measured/predicted temperature profiles of several points on the same layer, the second stage proposes a reduced order model (ROM) (intra-layer prediction model) to decompose and construct the temperature profiles of all points on the same layer, which could be used to build the temperature field of the entire layer. The training of ROM is performed with an extreme learning machine (ELM) for computational efficiency. Fifteen wire arc AM experiments and nine simulations are designed for thin walls with a fixed length and unidirectional printing of each layer. The test results indicate that the proposed prediction method could construct the thermal history of a yet-to-print layer within 0.1 seconds on a low-cost desktop computer. Meanwhile, the method has acceptable generalization capability in most cases from lower layers to higher layers in the same simulation, as well as from one simulation to a new simulation on different AM process parameters. More importantly, after fine-tuning the proposed method with limited experimental data, the relative errors of all predicted temperature profiles on a new experiment are smaller than 0.09, which demonstrates the applicability and generalization of the proposed two-stage thermal history prediction method in online applications for metal AM., Comment: 30 pages, 21 figures, 2 tables

Published
2023

12. Some preconditioning techniques for a class of double saddle point problems

Author

Bakrani, Fariba Balani, Bergamaschi, Luca, Martinez, Angeles, and Hajarian, Masoud

Subjects
Mathematics - Numerical Analysis, 65F10, 65F50
Abstract

In this paper, we describe and analyze the spectral properties of a number of exact block preconditioners for a class of double saddle point problems. Among all these, we consider an inexact version of a block triangular preconditioner providing extremely fast convergence of the FGMRES method. We develop a spectral analysis of the preconditioned matrix showing that the complex eigenvalues lie in a circle of center (1,0) and radius 1, while the real eigenvalues are described in terms of the roots of a third order polynomial with real coefficients. Numerical examples are reported to illustrate the efficiency of inexact versions of the proposed preconditioners, and to verify the theoretical bounds., Comment: 19 pages, 3 Figures

Published
2023

13. Machine Learning-Based Prediction Model for ICU Mortality After Continuous Renal Replacement Therapy Initiation in Children

Author

Sameer Thadani, MD, Tzu-Chun Wu, PhD, Danny T. Y. Wu, PhD, Aadil Kakajiwala, MD, Danielle E. Soranno, MD, Gerard Cortina, MD, Rachana Srivastava, MD, Katja M. Gist, DO, Shina Menon, MD, on behalf of the Worldwide Exploration of Renal Replacement Outcomes Collaborative in Kidney Diseases (WE-ROCK) Collaborators, Emily Ahern, CPNP, DNP, Ayse Akcan Arikan, MD, Issa Alhamoud, MD, Rashid Alobaidi, MD, MSc, Pilar Anton-Martin, MD, PhD, Shanthi S. Balani, MD, Matthew Barhight, MD, MS, Abby Basalely, MD, MS, Amee M. Bigelow, MD, MS, Gabriella Bottari, MD, Andrea Cappoli, MD, Abhishek Chakraborty, MD, Eileen A. Ciccia, MD, Michaela Collins, BA, Denise Colosimo, MD, Mihaela A. Damian, MD, MPH, Sara De la Mata Navazo, MD, Gabrielle DeAbreu, MD, Akash Deep, MD, Kathy L. Ding, BS, Kristin J. Dolan, MD, Lama Elbahlawan, MD, Sarah N. Fernandez Lafever, MD, PhD, Dana Y. Fuhrman, DO, MS, Ben Gelbart, MBBS, Katja M. Gist, DO, MSc, Stephen M. Gorga, MD, MSc, Francesco Guzzi, MD, Isabella Guzzo, MD, Taiki Haga, MD, Elizabeth Harvey, MD, Denise C. Hasson, MD, Taylor Hill-Horowitz, BS, Haleigh Inthavong, BS, MS, Catherine Joseph, MD, Ahmad Kaddourah, MD, MS, Aadil Kakajiwala, MD, MSCI, Aaron D. Kessel, MD, MS, Sarah Korn, DO, Kelli A. Krallman, BSN, MS, David M. Kwiatkowski, MD, Msc, Jasmine Lee, MSc, Laurance Lequier, MD, Tina Madani Kia, BS, Kenneth E. Mah, MD, MS, Eleonora Marinari, MD, Susan D. Martin, MD, Tahagod H. Mohamed, MD, Catherine Morgan, MD, MSc, Theresa A. Mottes, APRN, Melissa A. Muff-Luett, MD, Siva Namachivayam, MBBS, Tara M. Neumayr, MD, Jennifer Nhan, MD, MS, Abigail O’Rourke, MD, Nicholas J. Ollberding, PhD, Matthew G. Pinto, MD, Dua Qutob, MD, Valeria Raggi, MD, Stephanie Reynaud, MD, Zaccaria Ricci, MD, Zachary A. Rumlow, DO, María J. Santiago Lozano, MD, PhD, Emily See, MBBS, David T. Selewski, MD, MSCR, Carmela Serpe, MSc, PhD, Alyssa Serratore, RN, MsC, Ananya Shah, BS, Weiwen V. Shih, MD, H. Stella Shin, MD, Cara L. Slagle, MD, Sonia Solomon, DO, Natalja L. Stanski, MD, Michelle C. Starr, MD, MPH, Erin K. Stenson, MD, Amy E. Strong, MD, MSCE, Susan A. Taylor, MSc, Sameer V. Thadani, MD, Amanda M. Uber, DO, Brynna Van Wyk, ARNP, MSN, Tennille N. Webb, MD, MSPH, Huaiyu Zang, PhD, Emily E. Zangla, DO, and Michael Zappitelli, MD, MSc

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

BACKGROUND:. Continuous renal replacement therapy (CRRT) is the favored renal replacement therapy in critically ill patients. Predicting clinical outcomes for CRRT patients is difficult due to population heterogeneity, varying clinical practices, and limited sample sizes. OBJECTIVE:. We aimed to predict survival to ICUs and hospital discharge in children and young adults receiving CRRT using machine learning (ML) techniques. DERIVATION COHORT:. Patients less than 25 years of age receiving CRRT for acute kidney injury and/or volume overload from 2015 to 2021 (80%). VALIDATION COHORT:. Internal validation occurred in a testing group of patients from the dataset (20%). PREDICTION MODEL:. Retrospective international multicenter study utilizing an 80/20 training and testing cohort split, and logistic regression with L2 regularization (LR), decision tree, random forest (RF), gradient boosting machine, and support vector machine with linear kernel to predict ICU and hospital survival. Model performance was determined by the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC) due to the imbalance in the dataset. RESULTS:. Of the 933 patients included in this study, 538 (54%) were male with a median age of 8.97 years and interquartile range (1.81–15.0 yr). The ICU mortality was 35% and hospital mortality was 37%. The RF had the best performance for predicting ICU mortality (AUROC, 0.791 and AUPRC, 0.878) and LR for hospital mortality (AUROC, 0.777 and AUPRC, 0.859). The top two predictors of ICU survival were Pediatric Logistic Organ Dysfunction-2 score at CRRT initiation and admission diagnosis of respiratory failure. CONCLUSIONS:. These are the first ML models to predict survival at ICU and hospital discharge in children and young adults receiving CRRT. RF outperformed other models for predicting ICU mortality. Future studies should expand the input variables, conduct a more sophisticated feature selection, and use deep learning algorithms to generate more precise models.

Published
2024
Full Text
View/download PDF

15. Worldwide Exploration of Renal Replacement Outcomes Collaborative in Kidney Disease (WE-ROCK)

Author

Menon, Shina, Krallman, Kelli A, Arikan, Ayse A, Fuhrman, Dana Y, Gorga, Stephen M, Mottes, Theresa, Ollberding, Nicholas, Ricci, Zaccaria, Stanski, Natalja L, Selewski, David T, Soranno, Danielle E, Zappitelli, Michael, Zang, Huaiyu, Gist, Katja M, Investigators, WE-ROCK, Ahern, Emily, Arikan, Ayse Akcan, Alhamoud, Issa, Alobaidi, Rashid, Anton-Martin, Pilar, Balani, Shanthi S, Barhight, Matthew, Basalely, Abby, Bigelow, Amee M, Bottari, Gabriella, Cappoli, Andrea, Ciccia, Eileen A, Collins, Michaela, Colosimo, Denise, Cortina, Gerard, Damian, Mihaela A, De la Mata Navazo, Sara, DeAbreu, Gabrielle, Deep, Akash, Ding, Kathy L, Dolan, Kristin J, Lafever, Sarah N Fernandez, Gelbart, Ben, Guzzi, Francesco, Guzzo, Isabella, Haga, Taiki, Harvey, Elizabeth, Hasson, Denise C, Hill-Horowitz, Taylor, Inthavong, Haleigh, Joseph, Catherine, Kaddourah, Ahmad, Kakajiwala, Aadil, Kessel, Aaron D, Korn, Sarah, Kwiatkowski, David M, Lee, Jasmine, Lequier, Laurance, Kia, Tina Madani, Mah, Kenneth E, Marinari, Eleonora, Martin, Susan D, Mohamed, Tahagod H, Morgan, Catherine, Mottes, Theresa A, Muff-Luett, Melissa A, Namachivayam, Siva, Neumayr, Tara M, Nhan, Jennifer, O'Rourke, Abigail, Ollberding, Nicholas J, Pinto, Matthew G, Qutob, Dua, Raggi, Valeria, Reynaud, Stephanie, Rumlow, Zachary A, Lozano, María J Santiago, See, Emily, Serpe, Carmela, Serratore, Alyssa, Shah, Ananya, Shih, Weiwen V, Shin, H Stella, Slagle, Cara L, Solomon, Sonia, Srivastava, Rachana, Starr, Michelle C, Stenson, Erin K, Strong, Amy E, Taylor, Susan A, Thadani, Sameer V, Uber, Amanda M, Van Wyk, Brynna, Webb, Tennille N, and Zangla, Emily E

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Clinical Trials and Supportive Activities, Pediatric, Prevention, Kidney Disease, Clinical Research, Renal and urogenital, Good Health and Well Being, WE-ROCK Investigators, WE-ROCK, acute kidney injury, continuous renal replacement therapy, database, fluid overload, pediatric, Biomedical and clinical sciences, Health sciences
Abstract

IntroductionContinuous renal replacement therapy (CRRT) is used for the symptomatic management of acute kidney injury (AKI) and fluid overload (FO). Contemporary reports on pediatric CRRT are small and single center in design. Large international studies evaluating CRRT practice and outcomes are lacking. Herein, we describe the design of a multinational collaborative.MethodsThe Worldwide Exploration of Renal Replacement Outcomes Collaborative in Kidney Disease (WE-ROCK) is an international collaborative of pediatric specialists whose mission is to improve short- and long-term outcomes of children treated with CRRT. The aims of this multicenter retrospective study are to describe the epidemiology, liberation patterns, association of fluid balance and timing of CRRT initiation, and CRRT prescription with outcomes.ResultsWe included children (n = 996, 0-25 years) admitted to an intensive care unit (ICU) and treated with CRRT for AKI or FO at 32 centers (in 7 countries) from 2018 to 2021. Demographics and clinical characteristics before CRRT initiation, during the first 7 days of both CRRT, and liberation were collected. Outcomes include the following: (i) major adverse kidney events at 90 days (mortality, dialysis dependence, and persistent kidney dysfunction), and (ii) functional outcomes (functional stats scale).ConclusionThe retrospective WE-ROCK study represents the largest international registry of children receiving CRRT for AKI or FO. It will serve as a broad and invaluable resource for the field of pediatric critical care nephrology that will improve our understanding of practice heterogeneity and the association of CRRT with clinical and patient-centered outcomes. This will generate preliminary data for future interventional trials in this area.

Published
2023

16. White matter integrity changes in mild cognitive impairment associated with Aspirin use

Author

Atefeh Kashanizadeh, Mona Zamanpour, Sahar Oftadeh Balani, Atiyeh Janbozorgi, and Negin Noruozi

Subjects
alzheimer's disease, aspirin, dti, white matter, Neurology. Diseases of the nervous system, RC346-429
Abstract

Objectives: Alzheimer's disease (AD) represents a significant public health challenge, particularly as its prevalence is projected to rise sharply. Aspirin, known for its anti-inflammatory and antiplatelet properties, has been hypothesized to affect AD progression, although findings from observational studies and clinical trials remain inconsistent.Methods: This study utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to investigate the potential association between aspirin use and white matter (WM) microstructural changes in a cohort of 148 mild cognitive impairment (MCI) subjects. Diffusion tensor imaging (DTI) was employed to assess WM integrity, with fractional anisotropy (FA) and diffusivity metrics serving as primary outcomes. Statistical analyses were conducted using ANCOVA, adjusting for age, sex, APOE ε4 genotype, and MMSE score.Results: Aspirin users exhibited significantly higher FA values in the anterior corona radiata and left external capsule, alongside lower axial and radial diffusivity values in the right cingulum, indicating better-preserved WM microstructure compared to non-users.Conclusion: These findings suggest that aspirin may confer neuroprotective effects on WM in early AD, potentially delaying cognitive decline. Further research is warranted to confirm these results and explore the underlying mechanisms. Aspirin is widely prescribed to millions of adults, yet its impact on WM regions in the brain remains largely unclear. Further research is necessary to replicate these findings and to assess whether the effects of aspirin on WM structure could contribute to delaying or preventing cognitive decline.

Published
2024
Full Text
View/download PDF

19. Finite Element Analysis on the Biomechanical Stability of TPMS-Based Scaffolds for Large Segmental Femur Bone Defect

Author

Rajkumar, Verma, Abhishek, Yadav, Anupam, Ramkumar, Janakarajan, Balani, Kantesh, Ghosh, Arindam, Series Editor, Chua, Daniel, Series Editor, de Souza, Flavio Leandro, Series Editor, Aktas, Oral Cenk, Series Editor, Han, Yafang, Series Editor, Gong, Jianghong, Series Editor, Jawaid, Mohammad, Series Editor, Kumar, Ajay, editor, Srivatsan, T. S., editor, Ravi Sankar, Mamilla, editor, Venkaiah, N., editor, and Seetharamu, S., editor

Published
2024
Full Text
View/download PDF

22. The Association Between Vasopressin and Adverse Kidney Outcomes in Children and Young Adults Requiring Vasopressors on Continuous Renal Replacement Therapy

Author

Denise C. Hasson, MD, Katja M. Gist, DO, MSc, JangDong Seo, PhD, Erin K. Stenson, MD, Aaron Kessel, MD, MS, Taiki Haga, MD, MSc, Sara LaFever, MD, PhD, Maria Jose Santiago, MD, PhD, Matthew Barhight, MD, MS, David Selewski, MD, MSCR, Zaccaria Ricci, MD, Nicholas J. Ollberding, PhD, Natalja L. Stanski, MD, on behalf of the Worldwide Exploration of Renal Replacement Outcomes Collaborative in Kidney Disease (WE-ROCK) Collaborative, Emily Ahern, CPNP, DNP, Ayse Akcan Arikan, MD, Issa Alhamoud, MD, Rashid Alobaidi, MD, MSc, Pilar Anton-Martin, MD, PhD, Shanthi S. Balani, MD, Abby Basalely, MD, MS, Amee M. Bigelow, MD, MS, Gabriella Bottari, MD, Andrea Cappoli, MD, Eileen A. Ciccia, MD, Michaela Collins, BA, Denise Colosimo, MD, Gerard Cortina, MD, Mihaela A. Damian, MD, MPH, Sara De la Mata Navazo, MD, Gabrielle DeAbreu, MD, Akash Deep, MD, Kathy L. Ding, BS, Kristin J. Dolan, MD, Sarah N. Fernandez Lafever, MD, PhD, Dana Y. Fuhrman, DO, MS, Ben Gelbart, MBBS, Stephen M. Gorga, MD, MSc, Francesco Guzzi, MD, Isabella Guzzo, MD, Taiki Haga, MD, Elizabeth Harvey, MD, Taylor Hill-Horowitz, BS, Haleigh Inthavong, BS, MS, Catherine Joseph, MD, Ahmad Kaddourah, MD, MS, Aadil Kakajiwala, MD, MSCI, Aaron D. Kessel, MD, MS, Sarah Korn, DO, Kelli A. Krallman, BSN, MS, David M. Kwiatkowski, MD, Msc, Jasmine Lee, MSc, Laurance Lequier, MD, Tina Madani Kia, BS, Kenneth E. Mah, MD, MS, Eleonora Marinari, MD, Susan D. Martin, MD, Shina Menon, MD, Tahagod H. Mohamed, MD, Catherine Morgan, MD, MSc, Theresa A. Mottes, APRN, Melissa A. Muff-Luett, MD, Siva Namachivayam, MBBS, Tara M. Neumayr, MD, Jennifer Nhan Md, MS, Abigail O’Rourke, MD, Matthew G. Pinto, MD, Dua Qutob, MD, Valeria Raggi, MD, Stephanie Reynaud, MD, Zachary A. Rumlow, DO, María J. Santiago Lozano, MD, PhD, Emily See, MBBS, David T. Selewski, MD, MSCR, Carmela Serpe, MSc, PhD, Alyssa Serratore, RN, MsC, Ananya Shah, BS, Weiwen V. Shih, MD, H. Stella Shin, MD, Cara L. Slagle, MD, Sonia Solomon, DO, Danielle E. Soranno, MD, Rachana Srivastava, MD, Michelle C. Starr, MD, MPH, Amy E. Strong, MD, MSCE, Susan A. Taylor, MSc, Sameer V. Thadani, MD, Amanda M. Uber, DO, Brynna Van Wyk, ARNP, MSN, Tennille N. Webb, MD, MSPH, Huaiyu Zang, PhD, Emily E. Zangla, DO, Michael Zappitelli, MD, MSc, T. Christine, E. Alvarez, MHI, RN, Elizabeth Bixler, BS, Erica Blender Brown, MA, CRA, Cheryl L. Brown, BS, Ambra Burrell, BA, Anwesh Dash, BS, Jennifer L. Ehrlich, RN, MHA, Simrandeep Farma, HBSc, Kim Gahring, RN, BSN, CCRN, Barbara Gales, RN, Madison R. Hilgenkamp, Sonal Jain, MS, Kate Kanwar, BA, MS, Jennifer Lusk, BSN, RN, CCRN, Christopher J. Meyer, BA AA, Katherine Plomaritas, BSN, RN, Joshua Porter, BS, Jessica Potts, BSN, RN, Alyssa Serratore, BNurs, GDipNP(PIC), RN, MsC, Elizabeth Schneider, BS, Vidushi Sinha, BS, P. J. Strack, RN, BSN, CCRN, Sue Taylor, RN, Katherine Twombley, MD, Brynna Van Wyk, MSN, ARNP, CPNP, Samantha Wallace, MS, Janet Wang, BS, Megan Woods, BS, Marcia Zinger, RN, and Alison Zong, BS

Subjects
Medical emergencies. Critical care. Intensive care. First aid, RC86-88.9
Abstract

OBJECTIVES:. Continuous renal replacement therapy (CRRT) and shock are both associated with high morbidity and mortality in the ICU. Adult data suggest renoprotective effects of vasopressin vs. catecholamines (norepinephrine and epinephrine). We aimed to determine whether vasopressin use during CRRT was associated with improved kidney outcomes in children and young adults. DESIGN:. Secondary analysis of Worldwide Exploration of Renal Replacement Outcomes Collaborative in Kidney Disease (WE-ROCK), a multicenter, retrospective cohort study. SETTING:. Neonatal, cardiac, PICUs at 34 centers internationally from January 1, 2015, to December 31, 2021. PATIENTS/SUBJECTS:. Patients younger than 25 years receiving CRRT for acute kidney injury and/or fluid overload and requiring vasopressors. Patients receiving vasopressin were compared with patients receiving only norepinephrine/epinephrine. The impact of timing of vasopressin relative to CRRT start was assessed by categorizing patients as: early (on or before day 0), intermediate (days 1–2), and late (days 3–7). INTERVENTIONS:. None. MEASUREMENTS AND MAIN RESULTS:. Of 1016 patients, 665 (65%) required vasopressors in the first week of CRRT. Of 665, 248 (37%) received vasopressin, 473 (71%) experienced Major Adverse Kidney Events at 90 days (MAKE-90) (death, renal replacement therapy dependence, and/or > 125% increase in serum creatinine from baseline 90 days from CRRT initiation), and 195 (29%) liberated from CRRT on the first attempt within 28 days. Receipt of vasopressin was associated with higher odds of MAKE-90 (adjusted odds ratio [aOR], 1.80; 95% CI, 1.20–2.71; p = 0.005) but not liberation success. In the vasopressin group, intermediate/late initiation was associated with higher odds of MAKE-90 (aOR, 2.67; 95% CI, 1.17–6.11; p = 0.02) compared with early initiation. CONCLUSIONS:. Nearly two-thirds of children and young adults receiving CRRT required vasopressors, including over one-third who received vasopressin. Receipt of vasopressin was associated with more MAKE-90, although earlier initiation in those who received it appears beneficial. Prospective studies are needed to understand the appropriate timing, dose, and subpopulation for use of vasopressin.

Published
2024
Full Text
View/download PDF

23. Exploring Brain Activity in Different Mental Cognitive Workloads

Author

Sahar Oftadeh Balani, Ali Fawzi Al-Hussainy, Alhan Abd Al-Hassan Shalal, Mohammed Ubaid, Zinab Aluquaily, Jaafar Alamoori, and Saeid Motevalli

Subjects
Brain, Complexity Analysis, Cognition, Electroencephalography, Psychiatry, RC435-571
Abstract

Objective: Understanding neural mechanisms underlying cognitive workload is crucial for advancing our knowledge of human cognition and mental processes. In this study, we utilized electroencephalography (EEG) analysis to investigate brain activity associated with varying mental cognitive workloads from a psychological perspective. Method: We employed a publicly accessible EEG dataset consisting of a cohort of 36 healthy volunteers (75% female), aged 18 to 26 years, while the participants were at rest or engaged in an arithmetic task to explore mental cognitive workload. After preprocessing to reduce noise and various artifacts and to obtain a clean signal for every subject, functional connectivity and complexity features were calculated from EEGs through the coherence and permutation entropy algorithms, respectively. Then, repeated measures analysis of variance (ANOVA) was conducted to assess the differences in complexity and connectivity measures across various brain regions between the rest and task states. Results: Brain sites showed significant within-subject effects, and the interaction between states and channels was significant for connectivity values (F = 3.68, P = 0.034). Post hoc comparisons indicated that FP1-F7, FP1-F8 and FP1-Fz connectivity were significantly lower during the task state compared to the rest state (P < 0.05). Moreover, F4-P3, F4-P4, FP1-O1, FP2-O2, F3-O1, F4-O1, F8-O1, C4-O1, F3-O2, F4-O2, F7-O2, F8-O2, Fz-O1, Fz-O2, Cz-O1 and Fz-P4 connectivity were significantly higher during the arithmetic task state (P < 0.05). Furthermore, brain sites showed significant within-subject effects and the interaction between states and channels was significant for entropy values (F = 3.50, P = 0.041). Post hoc comparisons indicated that the permutation entropy was significantly higher in the FP1, T3, T4, P4 and Pz channels during the arithmetic task compared to the rest state (P < 0.05). Conclusion: During arithmetic tasks, the increased connectivity in the frontoparietal and frontooccipital networks and heightened complexity in the prefrontal, temporal and parietal lobes reflect the collaborative engagement of brain areas specialized in numerical processing, attention, working memory, cognitive control, and visual-spatial cognition. These changes in connectivity and complexity facilitate the integration of multiple cognitive processes essential for effective arithmetic problem-solving.

Published
2024
Full Text
View/download PDF

24. Prevention and management of CMV infection in pediatric solid organ transplant recipients

Author

Balani, Shanthi S, Sadiq, Sanober, Jensen, Chelsey J, and Kizilbash, Sarah J

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Infectious Diseases, Prevention, Transplantation, Pediatric, Organ Transplantation, Infection, Good Health and Well Being, opportunistic infections, pediatric solid organ transplant, cytomegalovirus treatment, cytomegalovirus prevention, cytomegalovirus emerging treatment, Paediatrics and Reproductive Medicine, Other Medical and Health Sciences, Paediatrics
Abstract

Human cytomegalovirus (CMV) remains one of the most common opportunistic infections following solid organ transplantation in children. CMV causes morbidity and mortality through direct tissue-invasive disease and indirect immunomodulatory effects. In recent years, several new agents have emerged for the prevention and treatment of CMV disease in solid organ transplant recipients. However, pediatric data remain scarce, and many of the treatments are extrapolated from the adult literature. Controversies exist about the type and duration of prophylactic therapies and the optimal dosing of antiviral agents. This review provides an up-to-date overview of treatment modalities used to prevent and treat CMV disease in solid organ transplant (SOT) recipients.

Published
2023

26. An Intelligent Method to Identify Effective Factors in Customers' Dissatisfaction in the Insurance Industry using Ensemble Learning

Author

Kamran Balani, Hossein Sadr, Ahmad Edalatpanah, Mahnaz Manteghipour, and Mojdeh Nazari

Subjects
insurance industry, marketing strategies, customer dissatisfaction, data mining, machine learning, Industrial engineering. Management engineering, T55.4-60.8
Abstract

Given the competitive market of the insurance industry, customer retention is one of the most important goals of insurance brokers. As a matter of fact, attracting a new customer as well as establishing a relationship with the insurer and gaining his trust requires a lot of money. However, the cost of attracting new customers is much more than retaining existing customers. Accordingly, marketing strategies have shifted from product-oriented and many companies have turned to customer relationship management.Companies and organizations have found that retaining their current customers as their most valuable asset is highly important. Therefore, the strategy of insurance companies is to first retain existing customers and then attract new customers. In this regard, identifying the effective factors in customer turnover is essential. In this paper, data mining methods are used to predict the factors affecting customer dissatisfaction. Based on the empirical results, it has been determined that the customer attraction channel, purchase history and place of insurer are important factors affecting customers dissatisfaction in the insurance industry, respectively.

Published
2024
Full Text
View/download PDF

27. Bariatric Surgery for Patients with Overweight/Obesity. A Comprehensive Grading Methodology and Network Metanalysis of Randomized Controlled Trials on Weight Loss Outcomes and Adverse Events

Author

De Luca, Maurizio, Zese, Monica, Silverii, Giovanni Antonio, Ragghianti, Benedetta, Bandini, Giulia, Forestieri, Pietro, Zappa, Marco Antonio, Navarra, Giuseppe, Foschi, Diego, Musella, Mario, Sarro, Giuliano, Pilone, Vincenzo, Facchiano, Enrico, Foletto, Mirto, Olmi, Stefano, Raffelli, Marco, Bellini, Rosario, Gentileschi, Paolo, Cerbone, Maria Rosaria, Grandone, Ilenia, Berardi, Giovanna, Di Lorenzo, Nicola, Lucchese, Marcello, Piazza, Luigi, Casella, Giovanni, Manno, Emilio, Zaccaroni, Alberto, Balani, Alessandro, Mannucci, Edoardo, and Monami, Matteo

Published
2023
Full Text
View/download PDF

31. Characteristics and Outcomes of Children and Young Adults With Sepsis Requiring Continuous Renal Replacement Therapy: A Comparative Analysis From the Worldwide Exploration of Renal Replacement Outcomes Collaborative in Kidney Disease (WE-ROCK)*

Author

Stanski, Natalja L., Gist, Katja M., Hasson, Denise, Stenson, Erin K., Seo, JangDong, Ollberding, Nicholas J., Muff-Luett, Melissa, Cortina, Gerard, Alobaidi, Rashid, See, Emily, Kaddourah, Ahmad, Fuhrman, Dana Y., Ahern, Emily, Akcan Arikan, Ayse, Alhamoud, Issa, Alobaidi, Rashid, Anton-Martin, Pilar, Balani, Shanthi S., Barhight, Matthew, Basalely, Abby, Bigelow, Amee M., Bottari, Gabriella, Cappoli, Andrea, Ciccia, Eileen A., Collins, Michaela, Colosimo, Denise, Cortina, Gerard, Damian, Mihaela A., De la Mata Navazo, Sara, DeAbreu, Gabrielle, Deep, Akash, Ding, Kathy L., Dolan, Kristin J., Fernandez Lafever, Sarah N., Fuhrman, Dana Y., Gelbart, Ben, Gist, Katja M., Gorga, Stephen M., Guzzi, Francesco, Guzzo, Isabella, Haga, Taiki, Harvey, Elizabeth, Hasson, Denise C., Hill-Horowitz, Taylor, Inthavong, Haleigh, Joseph, Catherine, Kaddourah, Ahmad, Kakajiwala, Aadil, Kessel, Aaron D., Korn, Sarah, Krallman, Kelli A., Kwiatkowski, David M., Lee, Jasmine, Lequier, Laurance, Madani Kia, Tina, Mah, Kenneth E., Marinari, Eleonora, Martin, Susan D., Menon, Shina, Mohamed, Tahagod H., Morgan, Catherine, Mottes, Theresa A., Muff-Luett, Melissa A., Namachivayam, Siva, Neumayr, Tara M., Nhan, Jennifer, O’Rourke, Abigail, Ollberding, Nicholas J., Pinto, Matthew G., Qutob, Dua, Raggi, Valeria, Reynaud, Stephanie, Ricci, Zaccaria, Rumlow, Zachary A., Santiago Lozano, María J., See, Emily, Selewski, David T., Serpe, Carmela, Serratore, Alyssa, Shah, Ananya, Shih, Weiwen V., Stella Shin, H., Slagle, Cara L., Solomon, Sonia, Soranno, Danielle E., Srivastava, Rachana, Stanski, Natalja L., Starr, Michelle C., Stenson, Erin K., Strong, Amy E., Taylor, Susan A., Thadani, Sameer V., Uber, Amanda M., Van Wyk, Brynna, Webb, Tennille N., Zang, Huaiyu, Zangla, Emily E., Zappitelli, Michael, Alvarez, T. Christine E., Bixler, Elizabeth, Brown, Erica Blender, Brown, Cheryl L., Burrell, Ambra, Dash, Anwesh, Ehrlich, Jennifer L., Farma, Simrandeep, Gahring, Kim, Gales, Barbara, Hilgenkamp, Madison R., Jain, Sonal, Kanwar, Kate, Lusk, Jennifer, Meyer, Christopher J., Plomaritas, Katherine, Porter, Joshua, Potts, Jessica, Serratore, Alyssa, Schneider, Elizabeth, Sinha, Vidushi, Strack, P. J., Taylor, Sue, Twombley, Katherine, Van Wyk, Brynna, Wallace, Samantha, Wang, Janet, Woods, Megan, Zinger, Marcia, and Zong, Alison

Published
2024
Full Text
View/download PDF

32. The Association Between Vasopressin and Adverse Kidney Outcomes in Children and Young Adults Requiring Vasopressors on Continuous Renal Replacement Therapy

Author

Hasson, Denise C., Gist, Katja M., Seo, JangDong, Stenson, Erin K., Kessel, Aaron, Haga, Taiki, LaFever, Sara, Santiago, Maria Jose, Barhight, Matthew, Selewski, David, Ricci, Zaccaria, Ollberding, Nicholas J., Stanski, Natalja L., Ahern, Emily, Akcan Arikan, Ayse, Alhamoud, Issa, Alobaidi, Rashid, Anton-Martin, Pilar, Balani, Shanthi S., Barhight, Matthew, Basalely, Abby, Bigelow, Amee M., Bottari, Gabriella, Cappoli, Andrea, Ciccia, Eileen A., Collins, Michaela, Colosimo, Denise, Cortina, Gerard, Damian, Mihaela A., De la Mata Navazo, Sara, DeAbreu, Gabrielle, Deep, Akash, Ding, Kathy L., Dolan, Kristin J., Fernandez Lafever, Sarah N., Fuhrman, Dana Y., Gelbart, Ben, Gist, Katja M., Gorga, Stephen M., Guzzi, Francesco, Guzzo, Isabella, Haga, Taiki, Harvey, Elizabeth, Hasson, Denise C., Hill-Horowitz, Taylor, Inthavong, Haleigh, Joseph, Catherine, Kaddourah, Ahmad, Kakajiwala, Aadil, Kessel, Aaron D., Korn, Sarah, Krallman, Kelli A., Kwiatkowski, David M., Lee, Jasmine, Lequier, Laurance, Madani Kia, Tina, Mah, Kenneth E., Marinari, Eleonora, Martin, Susan D., Menon, Shina, Mohamed, Tahagod H., Morgan, Catherine, Mottes, Theresa A., Muff-Luett, Melissa A., Namachivayam, Siva, Neumayr, Tara M., Nhan, Jennifer, O’Rourke, Abigail, Ollberding, Nicholas J., Pinto, Matthew G., Qutob, Dua, Raggi, Valeria, Reynaud, Stephanie, Ricci, Zaccaria, Rumlow, Zachary A., Santiago Lozano, María J., See, Emily, Selewski, David T., Serpe, Carmela, Serratore, Alyssa, Shah, Ananya, Shih, Weiwen V., Stella Shin, H., Slagle, Cara L., Solomon, Sonia, Soranno, Danielle E., Srivastava, Rachana, Stanski, Natalja L., Starr, Michelle C., Stenson, Erin K., Strong, Amy E., Taylor, Susan A., Thadani, Sameer V., Uber, Amanda M., Van Wyk, Brynna, Webb, Tennille N., Zang, Huaiyu, Zangla, Emily E., Zappitelli, Michael, Christine, T., Alvarez, E., Bixler, Elizabeth, Brown, Erica Blender, Brown, Cheryl L., Burrell, Ambra, Dash, Anwesh, Ehrlich, Jennifer L., Farma, Simrandeep, Gahring, Kim, Gales, Barbara, Hilgenkamp, Madison R., Jain, Sonal, Kanwar, Kate, Lusk, Jennifer, Meyer, Christopher J., Plomaritas, Katherine, Porter, Joshua, Potts, Jessica, Serratore, Alyssa, Schneider, Elizabeth, Sinha, Vidushi, Strack, P. J., Taylor, Sue, Twombley, Katherine, Van Wyk, Brynna, Wallace, Samantha, Wang, Janet, Woods, Megan, Zinger, Marcia, and Zong, Alison

Published
2024
Full Text
View/download PDF

33. Effectiveness of Physical Activity in the Management of Nonspecific Low Back Pain: A Systematic Review

Author

Alexandra Alonso-Sal, José Luís Alonso-Perez, María Dolores Sosa-Reina, Juan Antonio García-Noblejas-Fernández, Viren Gul Balani-Balani, Giacomo Rossettini, and Jorge Hugo Villafañe

Subjects
nonspecific low back pain, exercise, biopsychosocial factors, physical health, inflammatory biomarkers, Medicine (General), R5-920
Abstract

Background and Objectives: This systematic review evaluates the effectiveness of exercise interventions for managing nonspecific low back pain (NSLBP) and explores their impact on related biopsychosocial factors, physical health variables, and inflammatory biomarkers. Materials and Methods: A comprehensive search of five databases (PubMed, CINAHL, PEDro, SCOPUS, Cochrane Library) was conducted, covering studies from 2019 to 2024. Fifteen randomized controlled trials involving 1338 participants aged 18 to 65 years with NSLBP were included. Data extraction and quality assessment were performed independently by two reviewers using the PEDro scale, and risk of bias was evaluated using the Cochrane Risk-of-Bias tool (RoB 2.0). Results: Exercise significantly reduced pain intensity and improved biopsychosocial factors such as depression, disability, functionality, quality of life, and kinesiophobia. Additionally, it enhanced physical parameters like proprioception, muscle thickness, and physical performance. However, the review found insufficient evidence regarding the effects of exercise on inflammatory biomarkers in NSLBP patients. Conclusions: The findings suggest that physical exercise is an effective intervention for pain reduction and the improvement of overall health in NSLBP, though further research is needed to clarify its impact on inflammation.

Published
2024
Full Text
View/download PDF

35. Continuous Kidney Replacement Therapy and Survival in Children and Young Adults: Findings From the Multinational WE-ROCK Collaborative

Author

Ahern, Emily, Arikan, Ayse Akcan, Alhamoud, Issa, Alobaidi, Rashid, Anton-Martin, Pilar, Barhight, Matthew, Basalely, Abby, Bigelow, Amee M., Bottari, Gabriella, Collins, Michaela, Colosimo, Denise, Cortina, Gerard, Damian, Mihaela A., Navazo, Sara de la Mata, DeAbreu, Gabrielle, Deep, Akash, Ding, Kathy L., Dolan, Kristin J., Fernandez Lafever, Sarah N., Fuhrman, Dana Y., Gelbart, Ben, Gorga, Stephen M., Guzzi, Francesco, Guzzo, Isabella, Haga, Taiki, Harvey, Elizabeth, Hasson, Denise C., Hill-Horowitz, Taylor, Inthavong, Haleigh, Kaddourah, Ahmad, Korn, Sarah, Krallman, Kelli A., Kwiatkowski, David M., Lee, Jasmine, Lequier, Laurance, Kia, Tina Madani, Mah, Kenneth E., Marinari, Eleonora, Martin, Susan D., Mohamed, Tahagod H., Morgan, Catherine, Mottes, Theresa A., Namachivayam, Siva, Neumayr, Tara M., Nhan, Jennifer, O’Rourke, Abigail, Qutob, Dua, Raggi, Valeria, Ricci, Zaccaria, Rumlow, Zachary A., See, Emily, Selewski, David T., Serpe, Carmela, Serratore, Alyssa, Shah, Ananya, Shin, H. Stella, Soranno, Danielle E., Stanski, Natalja L., Stenson, Erin K., Strong, Amy E., Taylor, Susan A., Thadani, Sameer V., Uber, Amanda M., Van Wyk, Brynna, Zangla, Emily E., Zappitelli, Michael, Starr, Michelle C., Gist, Katja M., Zang, Huaiyu, Ollberding, Nicholas J., Balani, Shanthi, Cappoli, Andrea, Ciccia, Eileen, Joseph, Catherine, Kakajiwala, Aadil, Kessel, Aaron, Muff-Luett, Melissa, Santiago Lozano, María J., Pinto, Matthew, Reynaud, Stephanie, Solomon, Sonia, Slagle, Cara, Srivastava, Rachana, Shih, Weiwen V., Webb, Tennille, and Menon, Shina

Published
2024
Full Text
View/download PDF

40. Before the High Court: Planting the Yardstick: The Approach to Mandatory Minimum Sentences and the High Court Appeals in Delzotto and Hurt.

Author

Balani, Rohan

Subjects
Judicial process -- Laws, regulations and rules, Mandatory sentences -- Laws, regulations and rules, Appellate procedure -- Laws, regulations and rules, Child sexual abuse -- Laws, regulations and rules, Bahar v. The Queen ((2011) 45 W.A.R. 100 (W. Austl. C.A.)), Hurt v. The Queen ((2022) 18 A.C.T.L.R. 272 (Austl. Cap. Terr. C.A.)), R. v. Delzotto (2022 N.S.W.C.C.A. 117 (Ct. Crim. App.)), Government regulation, Australia. Criminal Code Act 1995 (sch. 1), Australia. Crimes Act 1914 (s. 16AAB)
Abstract

I Introduction The appeals to the High Court in Delzotto v The King (1) and Hurt v The King (2) come from the New South Wales Court of Criminal Appeal [...], In Delzotto v The King and Hurt v The King, the High Court of Australia must decide a fundamental question which will shape the approach to mandatory minimum sentences in the future, both in terms of their consideration in sentencing and their use generally by Parliament. The appeals offer the High Court an opportunity to clarify whether a sentencing judge must use a mandatory minimum penalty as a yardstick in the sentencing exercise or whether a mandatory minimum penalty is only relevant where the sentence arrived at after the usual exercise of the sentencing discretion is below the mandated minimum. In doing so, the High Court will necessarily consider the core principles underlying criminal sentencing in Australia as well as the need for consistency in sentencing in the future. This column considers the appeals and suggests that the approach adopted should involve the use of a minimum penalty as a yardstick as this approach is the only one which is consistent with established principles of criminal sentencing.

Published
2023

42. Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software

Author

Arvisais-Anhalt, Simone, Lehmann, Christoph U, Bishop, Justin A, Balani, Jyoti, Boutte, Laurie, Morales, Marjorie, Park, Jason Y, and Araj, Ellen

Subjects
Data Management and Data Science, Information and Computing Sciences, Information Systems, Biochemistry and Cell Biology, Bioinformatics and computational biology, Information systems
Abstract

Although the laboratory information system has largely solved the problem of storing anatomic pathology reports and disseminating their contents across the healthcare system, the retrospective query of anatomic pathology reports remains an area for improvement across laboratory information system vendors. Our institution desired the ability to query our repository of anatomic pathology reports for clinical, operational, research, and educational purposes. To address this need, we developed a full-text anatomic pathology search tool using the business intelligence software, Tableau. Our search tool allows users to query the 333,685 anatomic pathology reports from our institutional clinical relational database using the business intelligence tool's built-in regular expression functionality. Users securely access the search tool using any web browser, thereby avoiding the cost of installing or maintaining software on users' computers. This tool is laboratory information system vendor agnostic and as many institutions already subscribe to business intelligence software, we believe this solution could be easily reproduced at other institutions and in other clinical departments.

Published
2022

46. Longitudinal trend of urolithiasis incidence rates among world countries during past decades

Author

Nasrin Borumandnia, Payam Fattahi, Atefeh Talebi, Maryam Taheri, Mohammadamin Sabbagh Alvani, Mohammadreza Mafi Balani, Sadra Ashrafi, and Hamid Alavimajd

Subjects
Urolithiasis, GBD study, Longitudinal analysis, Growth mixture model, Diseases of the genitourinary system. Urology, RC870-923
Abstract

Abstract Introduction This study explores the trend of urolithiasis in various countries and categorizes the countries in terms of how their urolithiasis incidence rate has changed over time. Methods The incidence rate of urolithiasis in 204 countries from 1990 to 2019, extracted from the Global Burden of Disease study, has been analyzed. Results According to the results, all regions had experienced an increasing trend in urolithiasis rate, except for Eastern Europe, Central Europe, and Southeast Asia regions (decreasing rates of -71.4, -56.2, and -9.2 per 100000, respectively). Moreover, the Caribbean region had the highest increasing trend of urolithiasis rates, and Central Asia was in the next rank (increasing rate of 48.3 and 34.3 per 100,000, respectively, p-value

Published
2023
Full Text
View/download PDF

47. Root Resorption Patterns of Primary Mandibular Molars and Location of Premolar Successors Through Radiographs in Pakistani Population

Author

Sadaf Ali, Tasleem Hosein, Khizra Rehman, Rafia Ruaaz, Yasir Raza, and Pooja Balani

Subjects
Biochemistry, QD415-436, Dentistry, RK1-715, Therapeutics. Pharmacology, RM1-950, Medicine (General), R5-920
Abstract

Background: Primary teeth undergo physiological root resorption followed by eruption of their permanent successors. Roots of primary mandibular molars can have either symmetrical or asymmetrical resorption patterns. This study aimed to determine the frequency of root resorption patterns of primary mandibular molars and the position of premolar successors through radiographs in children. Methods: A total sample of 240 primary mandibular teeth from 140 patients (5-12 years) who visited the Paediatric Dentistry Department of Fatima Jinnah dental college were reviewed using radiographs. The root resorption patterns of primary mandibular molars and the location of the premolar successors were determined. Effect modifiers were controlled through stratification concerning age, gender, right or left side and presence of caries. Post-stratification chi-square analysis was used and p

Published
2024
Full Text
View/download PDF

50. Frontiers in Multi-functional Biomaterials for Hip Joint Application

Author

Nayak, Chinmayee, Balani, Kantesh, Ramachandran, Divakar, Editorial Board Member, Basu, Bikramjit, Editorial Board Member, Chattoraj, I, Editorial Board Member, Prasad, N. Eswara, Editorial Board Member, Manna, Indranil, Editorial Board Member, Gokhale, Amol A., Editorial Board Member, Reddy, G. Madhusudan, Editorial Board Member, Shrivastava, Amber, editor, Arora, Amit, editor, Srivastava, Chandan, editor, Dhawan, Nikhil, editor, and Shekhar Singh, Sudhanshu, editor

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results