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9. A Study of Machine Learning Models in Predicting the Intention of Adolescents to Smoke Cigarettes

Author

Nam, Seung Joon, Kim, Han Min, Kang, Thomas, and Park, Cheol Young

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The use of electronic cigarette (e-cigarette) is increasing among adolescents. This is problematic since consuming nicotine at an early age can cause harmful effects in developing teenager's brain and health. Additionally, the use of e-cigarette has a possibility of leading to the use of cigarettes, which is more severe. There were many researches about e-cigarette and cigarette that mostly focused on finding and analyzing causes of smoking using conventional statistics. However, there is a lack of research on developing prediction models, which is more applicable to anti-smoking campaign, about e-cigarette and cigarette. In this paper, we research the prediction models that can be used to predict an individual e-cigarette user's (including non-e-cigarette users) intention to smoke cigarettes, so that one can be early informed about the risk of going down the path of smoking cigarettes. To construct the prediction models, five machine learning (ML) algorithms are exploited and tested for their accuracy in predicting the intention to smoke cigarettes among never smokers using data from the 2018 National Youth Tobacco Survey (NYTS). In our investigation, the Gradient Boosting Classifier, one of the prediction models, shows the highest accuracy out of all the other models. Also, with the best prediction model, we made a public website that enables users to input information to predict their intentions of smoking cigarettes.

Published
2019

10. Kidney and Cardiovascular Effects of Canagliflozin According to Age and Sex: A Post Hoc Analysis of the CREDENCE Randomized Clinical Trial

Author

Perkovic, Vlado, Mahaffey, Kenneth W., Agarwal, Rajiv, Bakris, George, Brenner, Barry M., Cannon, Christopher P., Charytan, David M., de Zeeuw, Dick, Greene, Tom, Jardine, Meg J., Heerspink, Hiddo J.L., Levin, Adeera, Meininger, Gary, Neal, Bruce, Pollock, Carol, Wheeler, David C., Zhang, Hong, Zinman, Bernard, Jardine, Meg, Li, Nicole, Kolesnyk, Inna, Aizenberg, Diego, Pecoits-Filho, Roberto, Cherney, David, Obrador, Gregorio, Chertow, Glenn, Chang, Tara, Hawley, Carmel, Ji, Linong, Wada, Takashi, Jha, Vivekanand, Lim, Soo Kun, Lim-Abrahan, Mary Anne, Santos, Florence, Chae, Dong-Wan, Hwang, Shang-Jyh, Vazelov, Evgueniy, Rychlík, Ivan, Hadjadj, Samy, Krane, Vera, Rosivall, László, De Nicola, Luca, Dreval, Alexander, Nowicki, Michał, Schiller, Adalbert, Distiller, Larry, Górriz, Jose L., Kolesnyk, Mykola, David, Wheeler, C., Guerrero, Rodolfo Andres Ahuad, Albisu, Juan Pablo, Alvarisqueta, Andres, Bartolacci, Ines, Berli, Mario Alberto, Bordonava, Anselmo, Calella, Pedro, Cantero, Maria Cecilia, Cartasegna, Luis Rodolfo, Cercos, Esteban, Coloma, Gabriela Cecilia, Colombo, Hugo, Commendatore, Victor, Cuadrado, Jesus, Cuneo, Carlos Alberto, Cusumano, Ana Maria, Douthat, Walter Guillermo, Dran, Ricardo Dario, Farias, Eduardo, Fernandez, Maria Florencia, Finkelstein, Hernan, Fragale, Guillermo, Fretes, Jose Osvaldo, Garcia, Nestor Horacio, Gastaldi, Anibal, Gelersztein, Elizabeth, Glenny, Jorge Archibaldo, Gonzalez, Joaquin Pablo, Colaso, Patricia del Carmen Gonzalez, Goycoa, Claudia, Greloni, Gustavo Cristian, Guinsburg, Adrian, Hermida, Sonia, Juncos, Luis Isaias, Klyver, Maria Isabel, Kraft, Florencia, Krynski, Fernando, Lanchiotti, Paulina Virginia, Leon de la Fuente, Ricardo Alfonso, Marchetta, Nora, Mele, Pablo, Nicolai, Silvia, Novoa, Pablo Antonio, Orio, Silvia Ines, Otreras, Fabian, Oviedo, Alejandra, Raffaele, Pablo, Resk, Jorge Hector, Rista, Lucas, Papini, Nelson Rodriguez, Sala, Jorgelina, Santos, Juan Carlos, Schiavi, Lilia Beatriz, Sessa, Horacio, Casabella, Tomas Smith, Ulla, Maria Rosa, Valdez, Maria, Vallejos, Augusto, Villarino, Adriana, Visco, Virginia Esther, Wassermann, Alfredo, Zaidman, Cesar Javier, Cheung, Ngai Wah, Droste, Carolyn, Fraser, Ian, Johnson, David, Mah, Peak Mann, Nicholls, Kathy, Packham, David, Proietto, Joseph, Roberts, Anthony, Roger, Simon, Tsang, Venessa, Raduan, Roberto Abrão, Costa, Fernando Augusto Alves da, Amodeo, Celso, Turatti, Luiz Alberto Andreotti, Bregman, Rachel, Sanches, Fernanda Cristina Camelo, Canani, Luis Henrique, Chacra, Antônio Roberto, Borges, João Lindolfo Cunha, Vêncio, Sérgio Alberto Cunha, Franco, Roberto Jorge da Silva, d’Avila, Domingos, Portes, Evandro de Souza, de Souza, Pedro, Deboni, Luciane Mônica, Fraige Filho, Fadlo, Neto, Bruno Geloneze, Gomes, Marcus, Kohara, Suely Keiko, Keitel, Elizete, Saraiva, Jose Francisco Kerr, Lisboa, Hugo Roberto Kurtz, Contieri, Fabiana Loss de Carvalho, Milagres, Rosângela, Junior, Renan Montenegro, de Brito, Claudia Moreira, Hissa, Miguel Nasser, Sabbag, Ângela Regina Nazario, Noronha, Irene, Panarotto, Daniel, Filho, Roberto Pecoits, Pereira, Márcio Antônio, Saporito, Wladmir, Scotton, Antonio Scafuto, Schuch, Tiago, de Almeida, Roberto Simões, Ramos, Cássio Slompo, Felício, João Soares, Thomé, Fernando, Hachmann, Jean Carlo Tibes, Yamada, Sérgio, Hayashida, Cesar Yoiti, Petry, Tarissa Beatrice Zanata, Zanella, Maria Teresa, Andreeva, Viktoria, Angelova, Angelina, Dimitrov, Stefan, Genadieva, Veselka, Genova-Hristova, Gabriela, Hristozov, Kiril, Kamenov, Zdravko, Koundurdjiev, Atanas, Lozanov, Lachezar, Margaritov, Viktor, Nonchev, Boyan, Rangelov, Rangel, Shinkov, Alexander, Temelkova, Margarita, Velichkova, Ekaterina, Yakov, Andrian, Aggarwal, Naresh, Aronson, Ronnie, Bajaj, Harpreet, Chouinard, Guy, Conway, James, Cournoyer, Serge, DaRoza, Gerald, De Serres, Sacha, Dubé, François, Goldenberg, Ronald, Gupta, Anil, Gupta, Milan, Henein, Sam, Khandwala, Hasnain, Leiter, Lawrence, Madore, François, McMahon, Alan, Muirhead, Norman, Pichette, Vincent, Rabasa-Lhoret, Remi, Steele, Andrew, Tangri, Navdeep, Torshizi, Ali, Woo, Vincent, Zalunardo, Nadia, Montenegro, María Alicia Fernández, Gonzalo Godoy Jorquera, Juan, Fariña, Marcelo Medina, Gajardo, Victor Saavedra, Vejar, Margarita, Chen, Nan, Chen, Qinkai, Gan, Shenglian, Kong, Yaozhong, Li, Detian, Li, Wenge, Li, Xuemei, Lin, Hongli, Liu, Jian, Lu, Weiping, Mao, Hong, Ren, Yan, Song, Weihong, Sun, Jiao, Sun, Lin, Tu, Ping, Wang, Guixia, Yang, Jinkui, Yin, Aiping, Yu, Xueqing, Zhao, Minghui, Zheng, Hongguang, Mendoza, Jose Luis Accini, Arcos, Edgar, Avendano, Jorge, Diaz Ruiz, Jorge Ernesto Andres, Ortiz, Luis Hernando Garcia, Gonzalez, Alexander, Triana, Eric Hernandez, Higuera, Juan Diego, Malaver, Natalia, de Salazar, Dora Inés Molina, Rosero, Ricardo, Alexandra Terront Lozano, Monica, Cometa, Luis Valderrama, Valenzuela, Alex, Vargas Alonso, Ruben Dario, Villegas, Ivan, Yupanqui, Hernan, Bartaskova, Dagmar, Barton, Petr, Belobradkova, Jana, Dohnalova, Lenka, Drasnar, Tomas, Ferkl, Richard, Halciakova, Katarina, Klokocnikova, Vera, Kovar, Richard, Lastuvka, Jiri, Lukac, Martin, Pesickova, Satu, Peterka, Karel, Pumprla, Jiri, Rychlik, Ivan, Saudek, Frantisek, Tesar, Vladimir, Valis, Martin, Weiner, Pavel, Zemek, Stanislav, Alamartine, Eric, Borot, Sophie, Cariou, Bertrand, Dussol, Bertrand, Fauvel, Jean-Pierre, Gourdy, Pierre, Klein, Alexandre, Le Meur, Yannick, Penfornis, Alfred, Roussel, Ronan, Saulnier, Pierre-Jean, Thervet, Eric, Zaoui, Philippe, Burst, Volker, Faghih, Markus, Faulmann, Grit, Haller, Hermann, Jerwan-Keim, Reinhold, Maxeiner, Stephan, Paschen, Björn, Plassmann, Georg, Rose, Ludger, Gonzalez Orellana, Ronaldo Arturo, Haase, Franklin Paul, Moreira Diaz, Juan Pablo, Ramirez Roca, Luis Alberto, Sánchez Arenales, Jose Antonio, Sanchez Polo, José Vicente, Juarez, Erick Turcios, Csecsei, Gyongyi, Csiky, Botond, Danos, Peter, Deak, Laszlo, Dudas, Mihaly, Harcsa, Eleonora, Keltai, Katalin, Keresztesi, Sandor, Kiss, Krisztian, Konyves, Laszlo, Major, Lajos, Mileder, Margit, Molnar, Marta, Mucsi, Janos, Oroszlan, Tamas, Ory, Ivan, Paragh, Gyorgy, Peterfai, Eva, Petro, Gizella, Revesz, Katalin, Takacs, Robert, Vangel, Sandor, Vasas, Szilard, Zsom, Marianna, Abraham, Oomman, Bhushan, Raju Sree, Deepak, Dewan, Edwin, Fernando M., Gopalakrishnan, Natarajan, Gracious, Noble, Hansraj, Alva, Jain, Dinesh, Keshavamurthy, C.B., Khullar, Dinesh, Manisha, Sahay, Peringat, Jayameena, Prasad, Narayan, Satyanarayana, Rao K., Sreedhar, Reddy, Sreelatha, Melemadathil, Sudhakar, Bhimavarapu, Chandra Vyasam, Ramesh, Bonadonna, Riccardo, Castellino, Pietro, Ceriello, Antonio, Chiovato, Luca, De Cosmo, Salvatore, Derosa, Giuseppe, Di Carlo, Alberto, Di Cianni, Graziano, Frascà, Giovanni, Fuiano, Giorgio, Gambaro, Giovanni, Garibotto, Giacomo, Giorda, Carlo, Malberti, Fabio, Mandreoli, Marcora, Mannucci, Edoardo, Orsi, Emanuela, Piatti, Piermarco, Santoro, Domenico, Sasso, Ferdinando Carlo, Serviddio, Gaetano, Stella, Andrea, Trevisan, Roberto, Veronelli, Anna Maria, Zanoli, Luca, Akiyama, Hitoshi, Aoki, Hiromi, Asano, Akimichi, Iitsuka, Tadashi, Kajiyama, Shizuo, Kashine, Susumu, Kawada, Toshio, Kodera, Takamoto, Kono, Hiroshi, Koyama, Kazunori, Kumeda, Yasuro, Miyauchi, Shozo, Mizuyama, Kazuyuki, Niiya, Tetsuji, Oishi, Hiroko, Ota, Satoshi, Sakakibara, Terue, Takai, Masahiko, Tomonaga, Osamu, Tsujimoto, Mitsuru, Wakasugi, Masakiyo, Wakida, Yasushi, Watanabe, Takayuki, Yamada, Masayo, Yanagida, Kazuhiro, Yanase, Toshihiko, Yumita, Wataru, Gaupsiene, Egle, Kozloviene, Dalia, Navickas, Antanas, Urbanaviciene, Egle, Abdul Ghani, Rohana, Kadir, Khalid Abdul, Ali, Norsiah, Che Yusof, Mohd Daud, Gan, Chye Lee, Ismail, Mastura, Kong, Wei Yen, Lam, Swee Win, Lee, Li Yuan, Loh, Chek Loong, Manocha, Anita Bhajan, Ng, Kee Sing, Ahmad, Nik Nur Fatnoon Nik, Ratnasingam, Vanassa, Shudim, Saiful Shahrizal Bin, Vengadasalam, Paranthaman, Abraira Munoz, Luis David, Salazar, Melchor Alpizar, Cruz, Juan Baas, Soto, Mario Burgos, Ramos, Jose Chevaile, Wong, Alfredo Chew, Correa Rotter, Jose Ricardo, Escalante, Tonatiu Diaz, Enriquez Sosa, Favio Edmundo, Lozano, Fernando Flores, Flota Cervera, Luis Fernando, Baron, Paul Frenk, Ballesteros, Cecilia Garcia, Gomez Rangel, Jose David, Herrera Jimenez, Luis Enrique, Irizar Santana, Sergio Saul, Flores, Fernando Jimenez, Molina, Hugo Laviada, Luna Ceballos, Rosa Isela, del Campo Blanco, Belia Martin, Franco, Guadalupe Morales, Moreno Loza, Oscar Tarsicio, Rocha, Cynthia Mustieles, Vera, Gregorio Obrador, Castellanos, Ricardo Orozco, Calcaneo, Juan Peralta, Reyes Rosano, Miguel Angel, Pattzi, Hiromi Rodriguez, Guzman, Juan Rosas, Rucker Joerg, Isabel Erika, Saavedra Sanchez, Sandra Berenice, Sanchez Mijangos, Jose Hector, Sanson, Pablo Serrano, Tamayo y Orozco, Juan Alfredo, Chavez, Eloisa Tellez, Cepeda, Alejandro Valdes, Carrillo, Luis Venegas, Mesa, Juan Villagordoa, Escobedo, Rolando Zamarripa, Baker, John, Noonan, Paul, Scott, Russell, Walker, Robert, Watson, Edward, Williams, Michael, Young, Simon, Abejuela, Zaynab, Agra, Jeimeen, Aquitania, Grace, Caringal, Clodoaido, Comia, Rhea Severina, Santos, Lalaine Delos, Gomez, Olivert, Jimeno, Cecilia, Tan, Gerry, Tolentino, Marsha, Yao, Christy, Yap, Yvette Ethel, Lallaine Ygpuara, Ma. Dovie, Bijata-Bronisz, Renata, Hotlos, Lucyna, Januszewicz, Andrzej, Kaczmarek, Barbara, Kaminska, Anna, Lazuka, Lech, Madej, Andrzej, Mazur, Stanislaw, Mlodawska-Choluj, Dorota, Nowicki, Michal, Orlowska-Kowalik, Grazyna, Popenda, Grazyna, Rewerska, Barbara, Sowinski, Dariusz, Angelescu, Liliana Monica, Anghel, Veronica, Avram, Rodica-Ioana, Busegeanu, Mihaela-Magdalena, Cif, Adriana, Cosma, Dana, Crisan, Carmen, Demian, Luiza Despina, Ferariu, Ioana Emilia, Halmagyi, Ildiko, Hancu, Nicolae, Munteanu, Mircea, Negru, Doru, Onaca, Adriana Gabriela, Petrica, Ligia, Popa, Amorin Remus, Ranetti, Aurelian-Emil, Serafinceanu, Cristian, Toarba, Cristina, Agafyina, Alina, Barbarash, Olga, Barysheva, Olga, Chizhov, Daniil, Dobronravov, Vladimir, Glinkina, Irina, Grineva, Elena, Khirmanov, Vladimir, Kolmakova, Elena, Koroleva, Tatiana, Kvitkova, Liudmila, Marasaev, Viacheslav, Mkrtumyan, Ashot, Morugova, Tatiana, Nagibovich, Galina, Nagibovich, Oleg, Nedogoda, Sergei, Osipova, Irina, Raskina, Tatiana, Samoylova, Yulia, Sazonova, Olga, Shamkhalova, Minara, Shutemova, Elena, Shwartz, Yuriy, Uriasyev, Oleg, Vorobyev, Sergey, Zateyshchikova, Anna, Zateyshshikov, Dmitry, Zykova, Tatyana, Antic, Slobodan, Djordjevic, Miodrag, Kendereski, Aleksandra, Lalic, Katarina, Lalic, Nebojsa, Popovic-Radinovic, Vesna, Babikova, Jana, Benusova, Olga, Buganova, Ingrid, Culak, Jan, Dzupina, Andrej, Dzuponova, Jana, Fulop, Peter, Ilavska, Adriana, Martinka, Emil, Ochodnicka, Zuzana, Pella, Daniel, Smatanova, Iveta, Ahmed, Fayzal, Badat, Aysha, Breedt, Johannes, Distiller, Lawrence, Govender, Vimladhevi, Govender, Ravendran, Joshi, Mukesh, Jurgens, Jaco, Latiff, Gulam, Lombard, Landman, Mookadam, Mohamed, Ngcakani, Nomangesi, Nortje, Hendrik, Oosthuizen, Helena, Pillay-Ramaya, Larisha, Prozesky, Hans, Reddy, Jeevren, Rheeder, Paul, Seeber, Mary, Cho, Young Min, Jeong, In-Kyung, Kim, Sin Gon, Kim, Yeong Hoon, Kwon, Hyuk-Sang, Kwon, Min Jeong, Lee, Byung-Wan, Lee, JungEun, Lee, Moon-Kyu, Nam, Moon-Suk, Oh, Kook-Hwan, Park, Cheol- Young, Park, Sun-Hee, Yoon, Kun Ho, Garcia, Pere Alvarez, Mercadal, Luis Asmarats, Barrios, Clara, Castro, Fernando Cereto, Guldris, Secundino Cigarran, Lopez, Marta Dominguez, Egido de los Rios, Jesus, Fresnedo, Gema Fernandez, Serrano, Antonio Galan, Garcia, Isabel, Gonzalez Martinez, Francisco Javier, Jodar Gimeno, Jose Esteban, Mendoza, Manuel Lopez, Marin, Tamara Malek, Portillo, Cristobal Morales, Munar Vila, Maria Antonia, Torres, Manuel Muñoz, Iglesias, Javier Nieto, Perez, Jonay Pantoja, Vera, Merce Perez, Portoles Perez, Jose M., Quesada Simón, María Angustias, Canonge, Rafael Simo, Gonzalez, Alfonso Soto, Riera, Manel Terns, Tinahones Madueno, Francisco Jose, Plaza, Mercedes Velo, Chang, Chwen-Tzuei, Chuang, Lee-Ming, Hsia, Te-Lin, Hsieh, Chang-Hsun, Lin, Chih-Ching, Lu, Yung- Chuan, Sheu, Wayne H-H, Barna, Olga, Bilyk, Svitlana D., Botsyurko, Volodymyr, Dudar, Iryna, Fushtey, Ivan, Godlevska, Olga, Golovchenko, Oleksandr, Gyrina, Olga, Kazmirchuk, Anatoliy, Komisarenko, Iuliia, Korzh, Oleksii, Kravchun, Nonna, Legun, Oleg, Mankovskyy, Borys, Martynyuk, Liliya, Mostovoy, Yuriy, Pashkovska, Nataliia, Pererva, Larysa, Pertseva, Tetyana, Samoylov, Oleksandr, Smirnov, Ivan, Svyshchenko, Yevgeniya, Tomashkevych, Halyna, Topchii, Ivan, Tryshchuk, Nadiya, Tseluyko, Vira, Vizir, Vadym, Vlasenko, Maryna, Zlova, Tetiana, Zub, Liliia, Abusnana, Salah, Railey, Mohamed, Abouglila, Kamal, Ainsworth, Paul, Ali, Zishan, Arutchelvam, Vijayaraman, Barnard, Maria, Bellary, Srikanth, Davies, Emyr, Davies, Mark, Davies, Simon, Dawson, Alison, El Kossi, Mohsen, English, Patrick, Fraser, Donald, Gnudi, Luigi, Gunstone, Anthony, Hall, Timothy, Hanif, Wasim, Jackson, Alan, Johnson, Andrew, Joseph, Franklin, Krishnan, Singhan, Kumwenda, Mick, MacDougall, Iain, Nixon, Paul, O'Hare, Joseph, Philip, Sam, Ramtoola, Shenaz, Saxena, Manish, Sennik, Davesh, Simon, Godwin, Singh, Baldev, Stephens, Jeffrey, Strzelecka, Anna, Symonds, Rehan, Turner, Wayne, Wahba, Mona, Wakeling, John, Wheeler, David, Winocour, Peter, Abdallah, Joseph, Abdullah, Raied, Abramowitz, Matthew, Acosta, Idalia, Aiello, Joseph, Akright, Laura, Akyea-Djamson, Ayim, Alappan, Rajendran, Alicic, Radica, Al-Karadsheh, Amer, Allison, Dale Crawford, Arauz-Pacheco, Carlos, Arfeen, Shahabul, Arif, Ahmed, Arvind, Moogali, Atray, Naveen, Awad, Ahmed, Barnhill, Peggy, Barranco, Elizabeth, Barrera, Carlos, Beacom, Matthew, Behara, Venkata, Belo, Diogo, Bentley-Lewis, Rhonda, Berenguer, Ramon, Bermudez, Lidia, Bernardo, Marializa, Biscoveanu, Mihaela, Bowman-Stroud, Cynthia, Brandon, Donald, Brusco, Osvaldo, Busch, Robert, Canaan, Yamil, Chilito, Alicia, Christensen, Tom, Christiano, Cynthia, Christofides, Elena, Chuateco, Caroucel, Cohen, Kenneth, Cohen, Robert, Cohen-Stein, Debbie, Cook, Charles, Coyne, Daniel, Daboul, Nizar, Darwish, Riad, Daswani, Adarsh, Deck, Kenneth, Desouza, Cyrus, Dev, Devasmita, Dhillon, Monika, Dua, Sohan, Eder, Frank, Elosegui, Ana Maria, El-Shahawy, Mohamed, Ervin, John, Esquenazi, Alberto, Evans, John, Fishbane, Steven, Frias, Juan, Galindo-Ramos, Eugenia, Galphin, Claude, Ghazi, Adline, Gonzalez, Enrique, Gorson, David, Gowda, Anupama, Greco, Barbara, Grubb, Stephen, Gulati, Rakesh, Hammoud, Jamal, Handelsman, Stuart, Hartman, Israel, Hershon, Kenneth, Hiser, Daniel, Hon, George, Jacob, Radu, Jaime, Maria, Jamal, Aamir, Kaupke, Charles, Keightley, Gerald, Kern, Elizabeth, Khanna, Rakhi, Khitan, Zeid, Kim, Sun, Kopyt, Nelson, Kovesdy, Csaba, Krishna, Gopal, Kropp, Jeffrey (Jay), Kumar, Amrendra, Kumar, Jayant, Kumar, Neil, Kusnir, Jorge, Lane, Wendy, Lawrence, Mary, Lehrner, Lawrence, Lentz, John, Levinson, Dennis, Lewis, Derek, Liss, Kenneth, Maddux, Andreas, Maheshwari, Hiralal, Mandayam, Sreedhar, Marar, Isam, Mehta, Bhasker, Middleton, John, Mordujovich, Jorge, Moreda, Ramon, Moustafa, Moustafa, Trenche, Samuel Mujica, Narayanan, Mohanram, Narvarte, Javier, Nassar, Tareq, Newman, George, Nichol, Brian, Nicol, Philip, Nisnisan, Josier, Nossuli, A. Kaldun, Obialo, Chamberlain, Olelewe, Sarah, Oliver, Michael, O'Shaughnessy, Andrew, Padron, John, Pankhaniya, Rohit, Parker, Reginald, Patel, Devesh, Patel, Gnyandev, Patel, Nina, Pavon, Humberto, Perez, Armando, Perez, Carlos, Perlman, Alan, Pettis, Karlton, Pharr, Walter, Phillips, Andrea, Purighalla, Raman, Quesada-Suarez, Luis, Ranjan, Rajiv, Rastogi, Sanjeev, Reddy, Jakkidi, Rendell, Marc, Rich, Lisa, Robinson, Michael, Rodriguez, Hector, Rosas, Sylvia, Saba, Fadi, Sankaram, Rallabhandi, Sarin, Ravi, Schreiman, Robert, Scott, David, Sekkarie, Mohamed, Sensenbrenner, John, Shakeel, Muhammad, Shanik, Michael, Shaw, Sylvia, Smith, Stephen, Solomon, Richard, Sprague, Amy, Spry, Leslie, Suchinda, Pusadee, Sultan, Senan, Surampudi, Prasanth, Sussman, Sherry, Tan, Anjanette, Terrelonge, Antonio, Thompson, Michael, Trespalacios, Fernando, Trippe, Bruce, Trueba, Pilar, Twahirwa, Marcel, Updegrove, John, Van Buren, Peter, Vannorsdall, Mark, Varghese, Freemu, Velasquez-Mieyer, Pedro, Ventrapragada, Sailaja, Vukotic, Goga, Wadud, Khurram, Warren, Mark, Watson, Henry, Watts, Ronald, Weiner, Daniel, Welker, James, Welsh, Jean, Williams, Shelley, Zaniewski-Singh, Michelle, Yi, Tae Won, Smyth, Brendan, Di Tanna, Gian Luca, Arnott, Clare, Cardoza, Kathryn, and Kang, Amy

Published
2023
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11. Predictive Situation Awareness for Ebola Virus Disease using a Collective Intelligence Multi-Model Integration Platform: Bayes Cloud

Author

Park, Cheol Young, Matsumoto, Shou, Ha, Jubyung, and Park, YoungWon

Subjects
Computer Science - Artificial Intelligence, Physics - Physics and Society, Quantitative Biology - Populations and Evolution
Abstract

The humanity has been facing a plethora of challenges associated with infectious diseases, which kill more than 6 million people a year. Although continuous efforts have been applied to relieve the potential damages from such misfortunate events, it is unquestionable that there are many persisting challenges yet to overcome. One related issue we particularly address here is the assessment and prediction of such epidemics. In this field of study, traditional and ad-hoc models frequently fail to provide proper predictive situation awareness (PSAW), characterized by understanding the current situations and predicting the future situations. Comprehensive PSAW for infectious disease can support decision making and help to hinder disease spread. In this paper, we develop a computing system platform focusing on collective intelligence causal modeling, in order to support PSAW in the domain of infectious disease. Analyses of global epidemics require integration of multiple different data and models, which can be originated from multiple independent researchers. These models should be integrated to accurately assess and predict the infectious disease in terms of holistic view. The system shall provide three main functions: (1) collaborative causal modeling, (2) causal model integration, and (3) causal model reasoning. These functions are supported by subject-matter expert and artificial intelligence (AI), with uncertainty treatment. Subject-matter experts, as collective intelligence, develop causal models and integrate them as one joint causal model. The integrated causal model shall be used to reason about: (1) the past, regarding how the causal factors have occurred; (2) the present, regarding how the spread is going now; and (3) the future, regarding how it will proceed. Finally, we introduce one use case of predictive situation awareness for the Ebola virus disease.

Published
2019

12. Efficacy and safety of enavogliflozin versus dapagliflozin added to metformin plus gemigliptin treatment in patients with type 2 diabetes: a double-blind, randomized, comparator-active study: ENHANCE-D study

Author

Kim, Kyung-Soo, Han, Kyung Ah, Kim, Tae Nyun, Park, Cheol-Young, Park, Jung Hwan, Kim, Sang Yong, Kim, Yong Hyun, Song, Kee Ho, Kang, Eun Seok, Kim, Chul Sik, Koh, Gwanpyo, Kang, Jun Goo, Kim, Mi Kyung, Han, Ji Min, Kim, Nan Hee, Mok, Ji Oh, Lee, Jae Hyuk, Lim, Soo, Kim, Sang Soo, Kim, Tae Ho, Won, Kyu Chang, Lee, Ki Young, Cho, Jae Hyoung, Han, Ju Young, Kim, So Hun, Nah, Jae Jin, Song, Hwa Rang, Lee, Si Eun, and Kim, Sungrae

Published
2023
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14. Reference Model of Multi-Entity Bayesian Networks for Predictive Situation Awareness

Author

Park, Cheol Young and Laskey, Kathryn Blackmond

Subjects
Computer Science - Artificial Intelligence
Abstract

During the past quarter-century, situation awareness (SAW) has become a critical research theme, because of its importance. Since the concept of SAW was first introduced during World War I, various versions of SAW have been researched and introduced. Predictive Situation Awareness (PSAW) focuses on the ability to predict aspects of a temporally evolving situation over time. PSAW requires a formal representation and a reasoning method using such a representation. A Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BN) with First-Order Logic (FOL). MEBN can be used to represent uncertain situations (supported by BN) as well as complex situations (supported by FOL). Also, efficient reasoning algorithms for MEBN have been developed. MEBN can be a formal representation to support PSAW and has been used for several PSAW systems. Although several MEBN applications for PSAW exist, very little work can be found in the literature that attempts to generalize a MEBN model to support PSAW. In this research, we define a reference model for MEBN in PSAW, called a PSAW-MEBN reference model. The PSAW-MEBN reference model enables us to easily develop a MEBN model for PSAW by supporting the design of a MEBN model for PSAW. In this research, we introduce two example use cases using the PSAW-MEBN reference model to develop MEBN models to support PSAW: a Smart Manufacturing System and a Maritime Domain Awareness System.

Published
2018

15. MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model

Author

Park, Cheol Young and Laskey, Kathryn Blackmond

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BN) with First-Order Logic (FOL). MEBN has sufficient expressive power for general-purpose knowledge representation and reasoning. Developing a MEBN model to support a given application is a challenge, requiring definition of entities, relationships, random variables, conditional dependence relationships, and probability distributions. When available, data can be invaluable both to improve performance and to streamline development. By far the most common format for available data is the relational database (RDB). Relational databases describe and organize data according to the Relational Model (RM). Developing a MEBN model from data stored in an RDB therefore requires mapping between the two formalisms. This paper presents MEBN-RM, a set of mapping rules between key elements of MEBN and RM. We identify links between the two languages (RM and MEBN) and define four levels of mapping from elements of RM to elements of MEBN. These definitions are implemented in the MEBN-RM algorithm, which converts a relational schema in RM to a partial MEBN model. Through this research, the software has been released as a MEBN-RM open-source software tool. The method is illustrated through two example use cases using MEBN-RM to develop MEBN models: a Critical Infrastructure Defense System and a Smart Manufacturing System.

Published
2018
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16. Human-aided Multi-Entity Bayesian Networks Learning from Relational Data

Author

Park, Cheol Young and Laskey, Kathryn Blackmond

Subjects
Computer Science - Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

An Artificial Intelligence (AI) system is an autonomous system which emulates human mental and physical activities such as Observe, Orient, Decide, and Act, called the OODA process. An AI system performing the OODA process requires a semantically rich representation to handle a complex real world situation and ability to reason under uncertainty about the situation. Multi-Entity Bayesian Networks (MEBNs) combines First-Order Logic with Bayesian Networks for representing and reasoning about uncertainty in complex, knowledge-rich domains. MEBN goes beyond standard Bayesian networks to enable reasoning about an unknown number of entities interacting with each other in various types of relationships, a key requirement for the OODA process of an AI system. MEBN models have heretofore been constructed manually by a domain expert. However, manual MEBN modeling is labor-intensive and insufficiently agile. To address these problems, an efficient method is needed for MEBN modeling. One of the methods is to use machine learning to learn a MEBN model in whole or in part from data. In the era of Big Data, data-rich environments, characterized by uncertainty and complexity, have become ubiquitous. The larger the data sample is, the more accurate the results of the machine learning approach can be. Therefore, machine learning has potential to improve the quality of MEBN models as well as the effectiveness for MEBN modeling. In this research, we study a MEBN learning framework to develop a MEBN model from a combination of domain expert's knowledge and data. To evaluate the MEBN learning framework, we conduct an experiment to compare the MEBN learning framework and the existing manual MEBN modeling in terms of development efficiency.

Published
2018

17. Gaussian Mixture Reduction for Time-Constrained Approximate Inference in Hybrid Bayesian Networks

Author

Park, Cheol Young, Laskey, Kathryn Blackmond, Costa, Paulo C. G., and Matsumoto, Shou

Subjects
Computer Science - Artificial Intelligence
Abstract

Hybrid Bayesian Networks (HBNs), which contain both discrete and continuous variables, arise naturally in many application areas (e.g., image understanding, data fusion, medical diagnosis, fraud detection). This paper concerns inference in an important subclass of HBNs, the conditional Gaussian (CG) networks, in which all continuous random variables have Gaussian distributions and all children of continuous random variables must be continuous. Inference in CG networks can be NP-hard even for special-case structures, such as poly-trees, where inference in discrete Bayesian networks can be performed in polynomial time. Therefore, approximate inference is required. In approximate inference, it is often necessary to trade off accuracy against solution time. This paper presents an extension to the Hybrid Message Passing inference algorithm for general CG networks and an algorithm for optimizing its accuracy given a bound on computation time. The extended algorithm uses Gaussian mixture reduction to prevent an exponential increase in the number of Gaussian mixture components. The trade-off algorithm performs pre-processing to find optimal run-time settings for the extended algorithm. Experimental results for four CG networks compare performance of the extended algorithm with existing algorithms and show the optimal settings for these CG networks.

Published
2018
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22. Fenofibrate and risk of end‐stage renal disease: A nationwide cohort study.

Author

Hyun, Young Youl, Kim, Kyung‐Soo, Hong, Sangmo, Han, Kyungdo, and Park, Cheol‐Young

Subjects
GLOMERULAR filtration rate, CHRONIC kidney failure, KIDNEY diseases, FENOFIBRATE, RANDOMIZED controlled trials
Abstract

Aim: Previous studies have shown that fenofibrate improves outcomes such as albuminuria and estimated glomerular filtration rate decline. We hypothesize that fenofibrate has renoprotective effects and prevents or delays the development of end‐stage renal disease. The objective of this study is to investigate the risk of incident end‐stage renal disease in relation to fenofibrate treatment in patients who are already taking statins. Materials and Methods: We performed a nationwide population‐based cohort study using data from the Korea National Health Information Database from 2010 to 2017. Among adults using statins, 413 715 fenofibrate users were compared with 413 715 fenofibrate non‐users after 1:1 age, sex and triglyceride matching. The endpoint of this study was incident end‐stage renal disease. Results: During a median 3.96‐year follow‐up, the incidence per 1000 person years of end‐stage renal disease was lower in fenofibrate users than in fenofibrate non‐users (0.885 vs. 0.960, p < 0.0001). The hazard ratio for end‐stage renal disease was lower (0.763, 95% confidence interval 0.710–0.821) in fenofibrate users. This association was significant in patients with hypertension, proteinuria and an estimated glomerular filtration rate <60 mL/min/1.732. Conclusions: Fenofibrate use in patients taking statins with either hypertension, proteinuria, or decreased estimated glomerular filtration rate is associated with a low risk of incident end‐stage renal disease. To confirm the renoprotective effect of fenofibrate in chronic kidney disease, a randomized controlled trial is warranted. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Dual add‐on therapy of gemigliptin and dapagliflozin in patients with type 2 diabetes inadequately controlled with metformin alone: The SOLUTION 2 study.

Author

Han, Kyung Ah, Hwang, You‐Cheol, Moon, Shin Je, Cho, Ho Chan, Yoo, Hye Jin, Choi, Sung Hee, Chon, Suk, Kim, Kyoung‐Ah, Kim, Tae Nyun, Kang, Jun Goo, Park, Cheol‐Young, Won, Jong Chul, Cho, Eunjoo, Kim, Jeongyun, and Park, Kyong Soo

Subjects
TYPE 2 diabetes, GLYCEMIC control, URINARY tract infections, GENITALIA infections, BODY mass index
Abstract

Aim: To evaluate the efficacy and safety of gemigliptin and dapagliflozin dual add‐on therapy (GEMI + DAPA) to metformin in type 2 diabetes (T2D) patients who had inadequate glycaemic control on metformin alone, compared with a single add‐on of either gemigliptin (GEMI) or dapagliflozin (DAPA) to metformin. Materials and Methods: In this randomized, double‐blind, double‐dummy, active‐controlled, parallel‐group, phase 3 study, 469 T2D patients treated with a stable dose of metformin for 8 weeks or longer were randomized to receive GEMI + DAPA (n = 157) and either GEMI (n = 156) or DAPA (n = 156). The primary endpoint was change in HbA1c levels from baseline at week 24. Results: Baseline characteristics including body mass index and T2D duration were similar among groups. At week 24, the least square mean changes in HbA1c from baseline were −1.34% with GEMI + DAPA, −0.90% with GEMI (difference between GEMI + DAPA vs. GEMI −0.44% [95% confidence interval {CI}: −0.58% to −0.31%], P <.01) and −0.78% with DAPA (difference between GEMI + DAPA vs. DAPA −0.56% [95% CI: −0.69% to −0.42%], P <.01). Both upper CIs were less than 0, demonstrating the superiority of GEMI + DAPA for lowering HbA1c. The rates of responders achieving HbA1c less than 7% and less than 6.5% were greater with GEMI + DAPA (84.9%, 56.6%) than with GEMI (55.3%, 32.2%) and DAPA (49.3%, 15.3%). The incidence rate of adverse events was similar across groups, with low incidence rates of hypoglycaemia, urinary tract infection and genital infection. Conclusions: These results suggest that the addition of GEMI + DAPA to metformin as triple combination therapy was effective, safe and well‐tolerated, especially for T2D patients who experienced poor glycaemic control on metformin alone. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Outcomes with Finerenone in Participants with Stage 4 CKD and Type 2 Diabetes: A FIDELITY Subgroup Analysis

Author

Sarafidis, Pantelis, Agarwal, Rajiv, Pitt, Bertram, Wanner, Christoph, Filippatos, Gerasimos, Boletis, John, Tuttle, Katherine R., Ruilope, Luis M., Rossing, Peter, Toto, Robert, Anker, Stefan D., Liu, Zhi-Hong, Joseph, Amer, Ahlers, Christiane, Brinker, Meike, Lawatscheck, Robert, Bakris, George, Aizenberg, Diego, Bartolacci, Inés, Besada, Diego, Bittar, Julio, Chahin, Mariano, Elbert, Alicia, Gelersztein, Elizabeth, Liberman, Alberto, Maffei, Laura, Manghi, Federico Pérez, Sanabria, Hugo, Vallejos, Augusto, Viñes, Gloria, Wassermann, Alfredo, Abhayaratna, Walter, Acharya, Shamasunder, Ekinci, Elif, Lee, Darren, MacIsaac, Richard, Mah, Peak Mann, Nelson, Craig, Packham, David, Pape, Alexia, Roger, Simon, Stephenson, Hugo, Suranyi, Michael, Wittert, Gary, Vale, Elizabeth, Colman, Peter, Colquhoun, David, Ellis, Chris, Joshua, Kim, Pedagogos, Eugenia, Regal, Paul, Topliss, Duncan, Vandeleur, James, Verjans, Johan, Wittert, Gary, Wynne, Katie-Jane, Clodi, Martin, Ebenbichler, Christoph, Fliesser-Görzer, Evelyn, Hanusch, Ursula, Krebs, Michael, Lhotta, Karl, Ludvik, Bernhard, Mayer, Gert, Neudorfer, Peter, Paulweber, Bernhard, Prager, Rudolf, Preiß, Wolfgang, Prischl, Friedrich, Schernthaner, Gerit-Holger, Sourij, Harald, Wiesholzer, Martin, Drexel, Heinz, Oberbauer, Rainer, Schönherr, Hans-Robert, Doubel, Peter, Engelen, Wendy, Gillard, Pieter, Hougardy, Jean-Michel, Krzesinski, Jean-Marie, Maes, Bart, Speeckaert, Marijn, Stas, Koen, van Gaal, Luc, Vanbelleghem, Hilde, Duyck, Francis, Scheen, André, Antunes, Daniela, Botelho, Roberto, Brito, Claudia, Canani, Luis, Canziani, Maria Eugenia, Cerqueira, Maria, de Paula, Rogerio, Eliaschewitz, Freddy, Figueiredo, Carlos Eduardo, Forti, Adriana, Hissa, Miguel, Leite, Emerson Lima Maurilo, Jr, Noronha, Irene, Paolino, Bruno, Paschoalin, Nathalia, Paschoalin, Raphael, Filho, Roberto Pecoits, Pereira, Marcio, Portes, Evandro, Precoma, Dalton, Rea, Rosangela, Riella, Miguel, Salles, Joao Eduardo, Vasconcellos, Eduardo, Vencio, Sergio, Bacci, Marcelo, Maia, Lilia, Villacorta, Aline, Apostolova, Emiliya, Boshnyashka, Radostina, Farah, Ghassan, Georgiev, Dimitar, Gushterova, Valentina, Klyuchkova, Neli, Lucheva, Mariya, Manova, Petya, Minkova, Dotska, Nonchev, Boyan, Pichmanova, Mariyana, Prakova, Zhulieta, Rangelov, Rangel, Rashkov, Rosen, Stanchev, Pavel, Stoyanovska-Elencheva, Bilyana, Tagarev, Zhivko, Temelkova-Kurktschieva, Theodora, Vasileva, Svetla, Yoncheva-Mihaylova, Mariana, Marinchev, Angel, Miteva, Mariya, Barre, Paul, Carlson, Brian, Conway, James, Cournoyer, Serge, Dumas, Richard, Fikry, Sameh, Goluch, Richard, Hamet, Pavel, Hart, Randolph, Henein, Sam, Liutkus, Joanne, Madore, Francois, Martinho, Valdemar, Mazza, Giuseppe, McFarlane, Philip, Keefe, Dennis O′, Peterson, Sean, Schwartz, Daniel, Shu, Daniel, Steele, Andrew, Tellier, Guy, Tennankore, Karthik, Tobe, Sheldon, Tsoukas, George, Tytus, Richard, Vitou, Louise, Walsh, Michael, Weisnagel, Stanley, Wilderman, Igor, Yale, Jean-Francois, El Boreky, Fadia, Kelly, Alan, Leiter, Lawrence, Teitelbaum, Ivor, Cobos, Jorge, Godoy, Juan, González, Fernando, Lobos, Sergio, Palma, Juan Carlos, Prieto Dominguez, Juan Carlos, Reyes, Eliana, Romero, Carmen, Saavedra, Victor, Vega, Mario, Medina, Marcelo, Varleta, Paola, Bu, Ruifang, Cai, Hanqing, Chen, Nan, Chen, Qinkai, Chen, Dejun, Cheng, Jinluo, Dong, Youping, Dong, Junwu, Guan, Tianjun, Hao, Chuanming, Huang, Wen, Jiang, Fangfang, Lei, Minxiang, Li, Ling, Li, Zhonghe, Li, Xuemei, Li, Jingmei, Li, Yan, Liang, Xinling, Liang, Bo, Liu, Fang, Liu, Yinghong, Liu, Yuantao, Liu, Zhihong, Long, Gang, Lu, Guoyuan, Lu, Weiping, Lu, Yibing, Luo, Ping, Ma, Jianhua, Mo, Zhaohui, Niu, Jianying, Peng, Ai, Shen, Jiansong, Shen, Feixia, Shi, Bingyin, Su, Qing, Sun, Zhuxing, Tang, Shuifu, Tong, Nanwei, Wang, Hao, Wang, Xinjun, Wang, Guixia, Wang, Jianqin, Wang, Yangang, Wang, Li, Wei, Jiali, Wu, Tianfeng, Wu, Chaoqing, Xing, Changying, Xiong, Fei, Xu, Xudong, Xu, Ning, Yan, Tiekun, Yang, Jinkui, Yin, Aiping, Zeng, Longyi, Zhang, Hao, Zhang, Yanlin, Zhang, Ying, Zhao, Wenjing, Zhao, Zhiquan, Zheng, Hongguang, Zhong, Ling, Zhu, Dalong, Zhuang, Yongze, Du, Yuming, Fang, Yi, Guo, Weiying, Jiang, Sheng, Kuang, Jian, Li, Dongmei, Li, Hongmei, Li, Yinan, Li, Yuxiu, Liu, Jian, Liu, Yu, Miao, Heng, Peng, Wen, Wang, Lihua, Xu, Mingtong, Zhong, Liyong, Zhu, Jun, Arango, Clara, Barrera, Sandra, López, Nelly Beltrán, Benitez, Diego, Blanco, Guillermo, Cadena, Andrés, Coronel, Julian, Cure, Carlos, Durán, Carlos, González, Alexander, Guzmán, Gustavo, Hernández, Eric, Ibarra, Jaime, Jaramillo, Carlos, Jaramillo, Nicolás, Kattah, William, Molina, Dora, Sánchez, Gregorio, Terront, Mónica, Trujillo, Freddy, Urina, Miguel, Vargas, Ruben, Villegas, Iván, Yupanqui, Hernán, Arcos, Edgar, Aroca, Gustavo, Barreto, Germán, Bermudez, Andres, Botero, Rodrigo, Cárdenas, Tatiana, Figueroa, Wilmer, Jaramillo, Mónica, Liévano, Manuel, López, Mónica, Molina, Dora, Rosero, Ricardo, Trillos, Pedro, Dino Alferi, Brada, Michal, Brezina, Jiri, Bucek, Petr, Edelsberger, Tomas, Gulakova, Drahomira, Zapletalova, Jitka Hasalova, Hola, Olga, Hornova, Lucie, Houdova, Jana, Hrmova, Helena, Karasek, David, Kopecka, Sarka, Kovar, Richard, Krcova, Eva, Kuchar, Jiri, Kutejova, Vlasta, Lubanda, Hana, Matyasek, Ivo, Mokrejsova, Magdalena, Okenka, Libor, Prazny, Martin, Pumprla, Jiri, Tomanek, Pavel, Andersen, Ulla, Andries, Alin, Bech, Jesper, Faber, Jens, Gislason, Gunnar, Hangaard, Jørgen, Pacyk, Grzegorz Jaroslaw, Juhl, Claus, Krarup, Thure, Lindhardt, Morten, Madsbad, Sten, Nielsen, Joan, Pedersen-Bjergaard, Ulrik, Poulsen, Per, Rasmussen, Ole, Rossing, Peter, Schousboe, Karoline, Gram, Jeppe, Lauridsen, Thomas, Pedersen, Erling, Thorsteinsson, Birger, Flöjt, Päivi, Honkasalo, Mikko, Honkasalo, Mikko, Humaloja, Kari, Kananen, Kristiina, Kantola, Ilkka, Koistinen, Arvo, Korsoff, Pirkko, Lahtela, Jorma, Nieminen, Sakari, Nieminen, Tuomo, Sadeharju, Karita, Strand, Jorma, Sulosaari, Sakari, Cariou, Bertrand, Chantrel, François, Clavel, Sylvaine, Combe, Christian, Fauvel, Jean-Pierre, Gallouj, Karim, Gouet, Didier, Guerci, Bruno, Guerrot, Dominique, Hourmant, Maryvonne, Klein, Alexandre, Mariat, Christophe, Marre, Michel, Mesbah, Rafik, Le Meur, Yannick, Monier, Arnaud, Moranne, Olivier, Roussel, Ronan, Serusclat, Pierre, Vendrely, Benoit, Verges, Bruno, Zaoui, Philippe, Axthelm, Christoph, Bergmann, Andreas, Birkenfeld, Andreas L., Braun, Hermann, Busch, Klaus, Contzen, Christel, Degenhardt, Stefan, Derwahl, Karl, Giebel, Thomas, Hagenow, Andreas, Haller, Hermann, Hasslacher, Christoph, Horacek, Thomas, Jungmair, Wolfgang, Kloos, Christof, Koch, Thorsten, Krüger, Thilo, Mühlfeld, Anja, Müller, Joachim, Pfützner, Andreas, Pistrosch, Frank, Rinke, Andrea, Rose, Ludger, Rump, Lars, Schettler, Volker, Schiefke, Ingolf, Schlichthaar, Heike, Schröppel, Bernd, Schöll, Norbert, Schubert, Kristin, Schürholz, Thomas, Sigal, Helena, Stemler, Lutz, Strack, Georg, Täschner, Heidrun, Toursarkissian, Nicole, Tschöpe, Diethelm, Ulmer, Achim, van der Giet, Markus, Wanner, Christoph, Winkelmann, Bernhard R., Boletis, Ioannis, Dimitriadis, George, Hatziagelaki, Erifili, Iatrou, Christos, Ioannidis, Ioannis, Kounadi, Theodora, Makriniotou, Ioanna, Papadopoulou, Dorothea, Papagianni, Aikaterini, Passadakis, Ploumis, Piaditis, George, Stefanidis, Ioannis, Tai Pang Ip, Lee, Paul, Andrea Luk, On Yan, Ma, Ronald, Chow, Wing Sun, Wang, Angela, Yeung, Vincent, Bajcsi, Dora, Danos, Peter, Harcsa, Eleonora, Kalina, Akos, Kazup, Szilvia, Keltai, Katalin, Kirschner, Robert, Kiss, Julianna, Kovacs, Laszlo, Lamboy, Beata, Literati-Nagy, Botond, Mileder, Margit, Nagy, Laszlo, Noori, Ebrahim, Nyirati, Gabor, Petro, Gizella, Schneider, Karoly, Simon, Judit, Szocs, Albert, Vasas, Szilard, Wudi, Krisztina, Zilahi, Zsolt, Zsom, Marianna, Eustace, Joe, Holian, John, Reddan, Donal, Meara, Yvonne O′, Abramof Ness, Rosane, Adawi, Faiad, Armaly, Zaher, Atar, Shaul, Bashkin, Amir, Ben Chetrit, Sydney, Yanay, Noa Berar, Chernin, Gil, Darawsha, Mahmud, Efrati, Shai, Elias, Mazen, Farber, Evgeny, Glandt, Mariela, Grossman, Ehud, Halabi, Majdi, Harman-Boehm, Ilana, Khazim, Khaled, Liberty, Idit, Minuchin, Oscar, Mosenzon, Ofri, Nakhoul, Farid, Nimer, Assy, Schwartz, Doron, Wainstein, Julio, Yagil, Yoram, Zukermann, Robert, Avogaro, Angelo, Battaglia, Giovanni Giorgio, Bevilacqua, Maurizio Tiziano, Bonora, Enzo, Bossi, Carlo Antonio, Calabrò, Paolo, Cavalot, Franco Luigi, Cimino, Roberto, Cozzolino, Mario Gennaro, David, Salvatore, Emdin, Michele, Fiaccadori, Enrico, Fiorina, Paolo, Giorda, Carlo Bruno, Gregorini, Maria Cristina, La Manna, Gaetano, Maggi, Davide Carlo, Manti, Roberta, Meregalli, Giancarla, Pani, Antonello, Parvanova, Aneliy Ilieva, Perico, Norberto, Piatti, PierMarco, Pisani, Antonio, Pontiroli, Antonio Ettore, Ponzani, Paola, Santorelli, Gennaro, Santoro, Domenico, Scanziani, Renzo, Teatini, Ugo, Tonolo, Giancarlo, Trevisan, Roberto, Veronelli, Anna Maria, Viviani, Giorgio Luciano, Araki, Hideo, Bando, Yukihiro, Ebisui, Osamu, Fujita, Naruhiro, Fukasawa, Hirotaka, Furuya, Ryuichi, Hamamoto, Yoshiyuki, Hamasaki, Akihiro, Hasegawa, Kotaro, Hatazaki, Masahiro, Hayashi, Terumasa, Higashi, Takayuki, Hirohata, Yoshihide, Horinouchi, Shuji, Hoshi, Ayumu, Imoto, Hirofumi, Inagaki, Akemi, Inagaki, Masayuki, Inaguma, Daijo, Inoue, Toshihiko, Ishii, Masao, Ishiko, Tamayo, Isono, Motohide, Jinnouchi, Hideaki, Kanai, Hidetoshi, Kanda, Daisuke, Kanehara, Hideo, Kashima, Masayuki, Kataoka, Yuko, Katayama, Shigehiro, Kato, Kiyoe, Katsuki, Takeshi, Kawamitsu, Katsunori, Kawasaki, Satsuki, Kikuchi, Fumi, Kikuchi, Hidetoshi, Kishimoto, Rui, Kobayashi, Kunihisa, Koide, Junko, Komi, Rieko, Kubota, Miyuki, Kuriya, Genpei, Kurose, Takeshi, Kusano, Yoshiro, Hajime, Maeda, Matsubayashi, Sunao, Matsumoto, Kazunari, Matsumura, Naoya, Matsuo, Yasuto, Matsuoka, Naoki, Miyaoka, Hiroaki, Miyata, Satoshi, Morita, Takeshi, Murakami, Isao, Murao, Satoshi, Nakamura, Udai, Nakayama, Mikihiro, Nakazawa, Jun, Nohara, Sakae, Nomiyama, Takashi, Noritake, Masayuki, Oda, Yoshiaki, Ogiwara, Takayuki, Ohashi, Hiroshi, Okamoto, Hideki, Okino, Shinichi, Osonoi, Takeshi, Sasaki, Nobuhiro, Sayo, Yoshitaka, Sekigami, Taiji, Shibasaki, Taro, Shibata, Hirotaka, Shimoyama, Tatsushi, Shinoda, Junji, Sobajima, Hiroshi, Sugitatsu, Kazuya, Sugiura, Toshiyuki, Sugiyama, Toru, Suzuki, Daisuke, Suzuki, Hiroyuki, Suzuki, Masaaki, Takeda, Asami, Tanaka, Asami, Tanaka, Seiichi, Tsunematsu, Izumi, Ueda, Yasuo, Uekihara, Soichi, Ujihara, Makoto, Yajima, Ken, Yamada, Daishiro, Yamada, Masayo, Yamagata, Kazuo, Yamakawa, Ken, Yamakawa, Fumiko, Yamasaki, Yoshimitsu, Yambe, Yuko, Yanagida, Taihei, Yanai, Hidekatsu, Yanase, Toshihiko, Yasuda, Tetsuyuki, Kriauciuniene, Dovile, Lasiene, Jurate, Navickas, Antanas, Radzeviciene, Lina, Urbanaviciene, Egle, Urbonas, Gediminas, Velaviciene, Audrone, Abd Ghani, Rohana, Aziz, Nor Azizah, Lee, Li Yuan, Loh, Chek Loong, Ali, Norhaliza Mohd, Noor, Nurain Mohd, Fatnoon Nik Ahmad, Nik Nur, Ratnasingam, Jeyakantha, Halimi Bin Wan Hasan, Wan Hasnul, Izani Wan Mohamed, Wan Mohd, Khir, Rizmy Najme, Mohamad, Masni, Alexander Tan, Tong Boon, Avila Pardo, Sandro, Adrian, Miriam Bastidas, Wong, Alfredo Chew, Escobedo de la Peña, Jorge, Salmón, Guillermo Fanghänel, Gálvez, Guillermo González, Ochoa, Ramiro Gutiérrez, Santana, Saúl Irizar, Rovalo, Magdalena Madero, Machado, Gustavo Méndez, Ruiz, Luis Nevarez, Ibarra, Denisse Ramos, López, Gabriel Ramos, Reyna, Leobardo Sauque, Ortiz, Gustavo Solache, Ortiz, Rafael Valdez, Mesa, Juan Villagordoa, Salazar, Melchor Alpizar, Hernández, Pedro García, González, José, Soto, José Lazcano, Mendoza, Arturo Saldaña, Santana, Sergio Irizar, Vilchis, Elvira González, Bakker, R.C., Barendregt, J.N.M., Boonstra, A.H., Bos, Willem, Brouwer, C.B., Buren, M. van, Gansevoort, Ron, Kooy, Adriaan, Krekels, Marielle, Leendert, Ruud J.M. van, Lieverse, Louis A.G., Luik, P.T., Penne, E. Lars, Gregoor, Peter Smak, Vogt, Liffert, Born, Bert-Jan van den, John Baker, Crawford, Veronica, Cutfield, Rick, Dunn, Peter, Krebs, Jeremy, Nirmalaraj, Kingsley, Scott, Russell, Smuts, Nine, Titchener, Janet, Eriksen, Erik, Finnes, Trine, Høivik, Hans, Karlsson, Thomas, Munk, Peter Scott, Radtke, Maria, Risberg, Knut, Rocke, Jan, Solnør, Leidulv, Stenehjem, Aud-Eldrid, Tafjord, Anne-Beathe, Asprusten, Emil, Hagemeier, Robert, Høye, Kjetil, Selsås, Hilde, Thorup, Frode, Wium, Cecilie, Pamugas, Glenda, Panelo, Araceli, Perez, Ronald, Tanque, Maribel, Tirador, Louie, Villa, Michael, Bautista, Albert, Catindig, Elizabeth, Manalo, Carlo, Mirasol, Roberto, Butrymowicz, Patrycja, Ciechanowski, Kazimierz, Cieslik, Grazyna, Franek, Edward, Gumprecht, Janusz, Hoffmann, Michal, Krzykowska, Jolanta, Kurnatowska, Ilona, Landa, Katarzyna, Madrzejewski, Adam, Madziarska, Katarzyna, Mazur, Stanislaw, Napora, Piotr, Nowicki, Michal, Ocicka-Kozakiewicz, Anna, Rewerska, Barbara, Rusicka, Teresa, Ruxer, Jan, Skokowska, Ewa, Stankiewicz, Andrzej, Stompor, Tomasz, Tiuryn-Petrulewicz, Agnieszka, Wasilewska, Katarzyna, Wierusz-Wysocka, Bogna, Wnetrzak-Michalska, Renata, Jedynasty, Krystyna, Anand, Izabela Sein, Almeida, Edgar, Ballesteros, Rosa, Barreto, Carlos, Beirao, Idalina, Birne, Rita, Esteves, Cesar, Guia, Jose, Heitor, Susana, Marques, Olinda, Melo, Pedro, Nolasco, Fernando, Pereira, Amalia, Roque, Cristina, Rosario, Francisco, Silva, Gil, Silva, Ana, Teixeira e Costa, Fernando, Lobos, Ana Vila, Alves, Ana Rita, Brandao, Ilidio, Carvalho, Rui, Coelho, Joao, Lourenco, Ana, Matos, Pedro, Rosario, Vanisa, Neves, Joao Sergio, Cortes-Maisonet, Gregorio, Roman-Miranda, Amaury, Brito-Peguero, Yudit, Colon-Vega, Gildred, Albota, Adrian, Bala, Cornelia, Barbonta, Hortensia, Caceaune, Elena, Catrinoui, Doina, Constantin, Ciprian, Dumitrescu, Adriana, Mindrescu, Nicoleta, Mistode, Cristina, Negrisanu, Gabriela, Onaca, Adriana, Paveliu, Silvia, Pintilei, Ella, Pop, Lavinia, Popa, Amorin, Popescu, Alexandrina, Radulian, Gabriela, Szilagyi, Iosif, Turcu, Liana, Vacaru, Georgeta, Vlad, Adrian, Filimon, Adriana, Veresiu, Ioan, Antsiferov, Mikhail, Arkhipov, Mikhail, Babkin, Andrey, Barbarash, Olga, Baranov, Vitaliy, Chernyavskaya, Elena, Demko, Arkadiy, Dreval, Alexander, Edin, Anton, Ermakova, Polina, Fadeev, Valentin, Galyavich, Albert, Gaysina, Leyla, Gordeev, Ivan, Ipatko, Irina, Kalashnikova, Marina, Khalimov, Yuriy, Klimontov, Vadim, Kobalava, Zhanna, Kosmacheva, Elena, Koziolova, Natalya, Sergey Levashov, Lyudmila Kvitkova, Libis, Roman, Marasaev, Vyacheslav, Malykh, Natalia, Martynenko, Vladimir, Malyutina, Sofya, Merai, Imad, Mkrtumyan, Ashot, Nechaeva, Galina, Petunina, Nina, Palyutin, Shamil, Pimenov, Leonid, Rechkova, Elena, Rodionova, Tatyana, Rymar, Oksana, Sardinov, Ruslan, Semenova, Olga, Sherenkov, Alexander, Solovev, Oleg, Smolyarchuk, Elena, Strongin, Leonid, Ukhanova, Olga, Verlan, Nadezhda, Vorokhobina, Natalya, Yakhontov, Davyd, Yakushin, Sergey, Zakharova, Elena, Zalevskaya, Alsu, Zanozina, Olga, Zhdanova, Elena, Zhukova, Larisa, Zykova, Tatyana, Argunova, Yulia, Nikolaev, Konstantin, Villevalde, Svetlana, Fang Sum, Chee, Suhail, Sufi Muhummad, San Tan, Ru, Vathsala, Anantharaman, Wong, Edmund, Bee, Yong Mong, Babikova, Jana, Buganova, Ingrid, Dzupina, Andrej, Ochodnicka, Zuzana, Sosovec, Dalibor, Spodniakova, Denisa, Minarik, Peter, Fayzal Ahmed, Amod, Aslam, Bhana, Sindeep, Distiller, Larry, Jansen van Rensburg, Dirkie, Joshi, Mukesh, Joshi, Shaifali, Lakha, Deepak, Mitha, Essack, Podgorski, Gracjan, Ranjith, Naresh, Rayner, Brian, Rheeder, Paul, Sarvan, Mohamed, Seeber, Mary, Siebert, Heidi, Tayob, Mohammed, Trokis, Julien, Urbach, Dorothea, van Zyl, Louis, Jansen van Rensburg, Dirkie, Bum-Soon Choi, Choi, Moon Gi, Chung, ChoonHee, Hwang, YouCheol, Kim, ChongHwa, Kim, InJoo, Kim, JaeHyeon, Kim, SinGon, Kim, SungGyun, Kim, Tae Hee, Lee, WooJe, Lee, ByungWan, Lee, Kang Wook, Oh, Kook-Hwan, Oh, Ji Eun, Oh, Yun Kyu, Oh, Dong-Jin, Park, Junbeom, Shin, Seok Joon, Sung, Su-Ah, Yu, Jae Myung, Chung, HyeSoo, Huh, Ji Hye, Kang, JunGoo, Kim, ChulSik, Kim, HyeSoon, Kim, NamHoon, Lim, Soo, Cho, Young Min, Park, Cheol Young, Agraz, Irene, Ampudia, Francisco Javier, Bouarich, Hanane, Calero, Francesca, Castro, Cristina, Guldris, Secundino Cigarrán, Garrit, Josep Cruzado, de Álvaro, Fernando, Galcerán, Josep, Albarrán, Olga González, Jaras, Julio Hernández, Ibernón, Meritxell, Deben, Francisco Martínez, Ma, Esteban, Dolores Martínez, Pascual Izuel, José María, Martins, Judith, Mediavilla, Juan, Michán, Alfredo, Santos, Julio Pascual, Poch, Esteban, Rusillo, Manuel Polaina, Juan, Carlos Sánchez, Olmo, Rafael Santamaría, Segura de la Morena, José Julián, Soto, Alfonso, Troya, Maribel, Castro, Fernando Cereto, Fernández, Pablo Gómez, Sánchez, Laura Fuentes, Moya, Mercedes González, Marrero, Domingo Hernández, Maroto, Gonzalo Piedrola, Redón, Josep, Seron, Daniel, Bruchfeld, Annette, Curiac, Dan, Eliasson, Ken, Frank, Malin, Guron, Gregor, Hellberg, Olof, Hellgren, Margareta, Larnefeldt, Hans, Lindholm, Carl-Johan, Löndahl, Magnus, Rein-Hedin, Erik, Soveri, Inga, Spaak, Jonas, Tengmark, Bengt-Olov, Lif-Tiberg, Cornelia, Månflod, Johan, Nguyen, Han, Ackermann, Daniel, Bilz, Stefan, Burnier, Michel, Forster, Christian, Kalbermatter, Stefan, Kistler, Andreas, Pechère-Bertschi, Antoinette, Schultes, Bernd, Laimer, Markus, Rudofsky, Gottfried, Strey, Christopher, Wuerzner, Gregoire, Chiz-Tzung Chang, Hung, Cheng-Chieh, Jiang, Ju-Ying, Lee, Chien-Te, Lin, Shuei-Liong, Tarng, Der-Cherng, Tu, Shih-Te, Wu, Mai-Szu, Wu, Ming-Ju, Chuang, Lee-Ming, Deerochanawong, Chaicharn, Kitiyakara, Chagriya, Ophascharoensuk, Vuddhidej, Pongchaiyakul, Chatlert, Satirapoj, Bancha, Kosachunhanan, Natapong, Sritara, Piyamitr, Eren, Necmi, Gul, Ibrahim, Gulel, Okan, Kocyigit, Ismail, Kumbasar, Abdulbaki, Sahin, Idris, Sari, Ramazan, Sayin, Burak, Tavli, Talat, Ustundag, Sedat, Yenicerioglu, Yavuz, Badak, Ozer, Cayli, Murat, Oguz, Aytekin, Ozdogan, Oner, Sari, Ibrahim, Temizhan, Ahmet, Tigen, Mustafa, Turk, Ugur, Yilmaz, Huseyin, Yilmaz, Mehmet, Bondarets, Iryna, Botsyurko, Volodymyr, Chernikova, Viktoriia, Donets, Oleksandra, Fushtey, Ivan, Grachova, Mariia, Isayeva, Anna, Kogut, Dmytro, Komisarenko, Julia, Kravchun, Nonna, Malyar, Kateryna, Mankovsky, Borys, Martynyuk, Liliya, Maslyanko, Vitaliy, Myshanych, Halyna, Pererva, Larysa, Pertseva, Nataliia, Serhiyenko, Oleksandr, Smirnov, Ivan, Sokolova, Liubov, Stryzhak, Vasyl, Vlasenko, Maryna, Isayeva, Ganna, Larin, Oleksandr, Ahmad AbouSaleh, Barratt, Jonathan, Dang, Cuong, Kahal, Hassan, Kirk, Adam, Kilvert, Anne, Kon, Sui Phi, McCafferty, Kieran, Patel, Dipesh, Rice, Sam, Vijayaraman, Arutchelvam, Wong, Yuk-ki, Gibson, Martin, Wahba, Mona, Zaidi, Reza, Bilous, Rudy, Johnson, Andrew, Kalathil, Dhanya, Kilvert, Anne, Kyriakidou, Christina, Mathew, Amit, Mukhtar, Rasha, Munsoor, Imrozia, Poterajlo, Anton, Swift, Pauline, Idalia Acosta, Adams, Atoya, 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Francisco, Gore, Ashwini, Grant, David, Habwe, Violet, Hamilton, Maxine, Hammoud, Jamal, Handelsman, Stuart, Hartman, Israel, Heigerick, Glenn, Henry, Andrew, Hernandez, German, Hernandez-Cassis, Carlos, Herrera, Carlos, Hertel, Joachim, Huang, Wenyu, Iglesias, Rogelio, Iranmanesh, Ali, Jackson, Timothy, Jain, Mahendra, Jamerson, Kenneth, Johnson, Karen, Judd, Eric, Kaplan, Joshua, Kayali, Zeid, Khan, Bobby, Khan, Muhammad, Kharait, Sourabh, Kirkman, M. Sue, Kopyt, Nelson, Kotzker, Wayne, Kovesdy, Csaba, Kreit, Camil, Krishna, Arvind, Kronfli, Saeed, Lee, Keung, LeJeune, Derek, Lemus, Brenda, Leon-Forero, Carlos, Linfert, Douglas, Lora, Henry, Lurie, Alexander, Maddukuri, Geetha, Magno, Alexander, Maletz, Louis, Mandayam, Sreedhar, Markell, Mariana, Mayfield, Ronald, Mbogua, Caroline, McMullen, Dierdre, Meisner, Carl, Minton, Stephen, Mocherla, Bharat, Mohandas, Rajesh, Montero, Manuel, Moustafa, Moustafa, Nadkarni, Salil, Nakhle, Samer, Navarro, Jesus, Neyra, Nilda, Nica, Romanita, Nicol, Philip, Norwood, Paul, Numrungroad, Visal, Donovan, Richard O′, Odugbesan, A., Paoli-Bruno, Jorge, Parikh, Samir, Patel, Rakesh, Peixoto, Aldo, Pergola, Pablo, Perlman, Alan, Pettis, Karlton, Pisoni, Roberto, Ponduchi, Mirela, Posada, Jorge, Prabhakar, Sharma, Radhakrishnan, Jai, Rahman, Mahboob, Raina, Rupesh, Rastogi, Anjay, Reisin, Efrain, Rendell, Marc, Robertson, David, Rocco, Michael, Romeu, Hugo, Rosas, Sylvia, Rosenfeld, Jack, Ross, Dennis, Rothman, Jeffrey, Rudolph, Lance, Ruhullah, Yusuf, Ruoff, Gary, Ryu, Jeffrey, Sahani, Mandeep, Sam, Ramin, Samuels, Garfield, Sanchez, William, Santos, Vladimir, Satko, Scott, Saxena, Sanjeev, Scott, David, Seco, Gilberto, Seek, Melvin, Serota, Harvey, Shafi, Tariq, Shahid, Nauman, Shanik, Michael, Sharma, Santosh, Sinha, Arjun, Smelser, James, Smith, Mark, Soe, Kyaw, Solomon, Richard, Soroka, Eugene, Soufer, Joseph, Spinowitz, Bruce, Spry, Leslie, Suarez, Rosa, Subramanian, Bala, Szerlip, Harold, Tamirisa, Aparna, Thomson, Stephen, Tran, Tuan-Huy, Treger, Richard, Trullenque, Gretel, Turk, Thomas, Umpierrez, Guillermo, Urbach, Daniel, Valdes, Martin, Valika, Shujauddin, Vega, Damaris, Weissman, Peter, Whaley-Connell, Adam, Winston, Jonathan, Wise, Jonathan, Wynne, Alan, Zeig, Steven, Abdel-Rahman, Emaad, Abreu, Edel, Awad, Alaa, Bahri, Nader, Bertsch, John, Bleich, David, Bornfreund, Jonathan, Brar, Harjeet, Brian, Susan, Brinson, Cynthia, Bruschetta, Humberto, Carpio, Jose, Cohen, Steven, Cosby, John, Dhanireddy, Soni, Diaz, Jorge, Dunn, Fredrick, Eppanapally, Sabitha, Fayad, Joseph, Goel, Archana, Govindaraju, Kanakadurga, Halpern, Stephen, Jones, Audrey, Kaye, William, Knight, Herbert, Koch, Stanley, Kohli, Nandini, Lastra, Guido, Lerman, Sam, Loredo, Jorge, Lovre, Dragana, Mandviwala, Mustafa, Martin, Earl, Meyer, Jill, Murray, John, Oliver, David, Oparil, Suzanne, Penabad, Jesus, Pereira, Isabel, Popeil, Larry, Quesada, Gonzalo, Ramanathan, Kodangudi, Ramos-Gonez, Luis, Rastegar, Mandana, Rastogi, Padmashri, Rondon, Juan, Roy-Chaudhury, Prabir, Smith, David, Williamson, Don, Womack, Catherine, Yamout, Hala, Yuryev, Michael, Chu, Phuong, Van Hoang, Lam, Khanh, Tran, Phi Nga, Nguyen Thi, Son, Pham Nguyen, Tran, Lan Phuong, Le, Thuy Khuong, Nguyen, Boi Ngoc, Nguyen, Thao, Nui, Nguyen Minh, Nam, Tran Quang, and Tran, Kim Chi

Published
2023
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39. Toward maximum energy density enabled by anode‐free lithium metal batteries: Recent progress and perspective.

Author

Park, Cheol‐Young, Kim, Jinuk, Lim, Won‐Gwang, and Lee, Jinwoo

Subjects
LITHIUM cells, ENERGY density, ENERGY storage, DENDRITES, ELECTRIC vehicles
Abstract

Owing to the emergenceof energy storage and electric vehicles, the desire for safe high‐energy‐density energy storage devices has increased research interest in anode‐free lithium metal batteries (AFLMBs). Unlike general lithium metal batteries (LMBs), in which excess Li exists to compensate for the irreversible loss of Li, only the current collector is employed as an anode and paired with a lithiated cathode in the fabrication of AFLMBs. Owing to their unique cell configuration, AFLMBs have attractive characteristics, including the highest energy density, safety, and cost‐effectiveness. However, developing AFLMBs with extended cyclability remains an issue for practical applications because the high reactivity of Li with limited inventory causes severely low Coulombic efficiency (CE), poor cyclability, and dendrite growth. To address these issues, tremendous effort has been devoted to stabilizing Li metal anodes for AFLMBs. In this review, the importance and challenges of AFLMBs are highlighted. Then, diverse strategies, such as current collectors modification, advanced electrolytes, cathode engineering, and operation protocols are thoroughly reviewed. Finally, a future perspective on the strategy is provided for insight into the basis of future research. It is hoped that this review provides a comprehensive understanding by reviewing previous research and arousing more interest in this field. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Coronary Artery Calcium Score as a Sensitive Indicator of Cardiovascular Disease in Patients with Type 2 Diabetes Mellitus: A Long-Term Cohort Study

Author

Koo, Dae-Jeong, primary, Lee, Mi Yeon, additional, Moon, Sun Joon, additional, Kwon, Hyemi, additional, Lee, Sang Min, additional, Park, Se Eun, additional, Park, Cheol-Young, additional, Lee, Won-Young, additional, Oh, Ki Won, additional, Cho, Sung Rae, additional, Jeong, Young-Hoon, additional, and Rhee, Eun-Jung, additional

Published
2023
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42. Efficacy and Safety of Evogliptin Add-on Therapy to Dapagliflozin/Metformin Combinations in Patients with Poorly Controlled Type 2 Diabetes Mellitus: A 24-Week Multicenter Randomized Placebo-Controlled Parallel-Design Phase-3 Trial with a 28-Week Extension

Author

Moon, Jun Sung, primary, Park, Il Rae, additional, Kim, Hae Jin, additional, Chung, Choon Hee, additional, Won, Kyu Chang, additional, Han, Kyung Ah, additional, Park, Cheol-Young, additional, Won, Jong Chul, additional, Kim, Dong Jun, additional, Koh, Gwan Pyo, additional, Kim, Eun Sook, additional, Yu, Jae Myung, additional, Hong, Eun-Gyoung, additional, Lee, Chang Beom, additional, and Yoon, Kun-Ho, additional

Published
2023
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50. Effect of Voluntary Participation on Mobile Health Care in Diabetes Management: Randomized Controlled Open-Label Trial

Author

Lee, Da Young, Yoo, Seung-Hyun, Min, Kyong Pil, and Park, Cheol-Young

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundThe role of mobile health care (mHealth) in glycemic control has been investigated, but its impact on self-management skills and its psychological aspects have not been studied. ObjectiveWe evaluated the efficacy of mHealth-based diabetes self-management education and the effect of voluntary participation on its effects. MethodsThis study was a randomized controlled open-label trial conducted for 6 months at Kangbuk Samsung Hospital. Participants in the control group (n=31) maintained their previous diabetes management strategies. Participants in the intervention group (n=41) additionally received mHealth-based diabetes self-management education through a mobile app and regular individualized feedback from health care professionals. The primary outcome was change in glycated hemoglobin (HbA1c) level over 6 months between the 2 groups (intervention versus control) and within each group (at 6 months versus baseline). The secondary outcomes were changes in body mass index, blood pressure, lipid profile, and questionnaire scores (the Korean version of the Summary of Diabetes Self-Care Activities Questionnaire, an Audit of Diabetes Dependent Quality of Life, the Appraisal of Diabetes Scale, and Problem Areas in Diabetes) over 6 months between groups and within each group. ResultsA total of 66 participants completed this study. HbA1c (P=.04), total cholesterol level (P=.04), and Problem Areas in Diabetes scores (P=.02) significantly decreased; total diet (P=.03) and self-monitoring of blood glucose level scores (P=.01), based on the Summary of Diabetes Self-Care Activities Questionnaire, markedly increased within the intervention group. These significant changes were observed in self-motivated participants who were recruited voluntarily via advertisements. ConclusionsmHealth-based diabetes self-management education was effective at improving glycemic control and diabetes self-management skills and lowering diabetes-related distress in voluntary participants. Trial RegistrationClinicalTrials.gov NCT03468283; http://clinicaltrials.gov/ct2/show/NCT03468283

Published
2020
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