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1. The practice and prospect of algorithm-driven virtual simulation technology in medical undergraduate education

Author

Tao Lili and Tao Qianshan

Subjects
virtual simulation technology, network model optimization, cloud computing, teaching experiment platform, medical education, 97p10, Mathematics, QA1-939
Abstract

Amid growing interest in the use of virtual simulation platforms in educational settings, the reform of medical education increasingly looks to virtual simulation technology as a promising new avenue. This study aims first to analyze the components of a virtual simulation system and to enhance the functionality of virtual simulation technology by optimizing the network model algorithm. Utilizing cloud computing technology, a virtual simulation teaching experiment platform was constructed. Further, a virtual simulation medical education system based on the BOPPPS teaching model was developed to address the constraints of practical experience in the traditional undergraduate medical education model. Empirical analysis of the virtual simulation medical education mode reveals that the CPU utilization rate on the constructed cloud platform ranged from 2% to 35%, and the memory usage varied between 15 and 25 GB. In comparative assessments of medical education practices, this study found that students trained under the virtual simulation technology-enhanced model scored 0.96 to 1.53 points higher in various skill assessments than those trained under traditional methods. Moreover, the total scores for communication abilities increased by 5.48 points, highlighting a significant improvement. These results affirm the superiority of the virtual simulation technology medical education model presented in this study. They underscore its practicality and feasibility for application and development in undergraduate medical education, providing a substantive pathway for integrating advanced virtual simulation technologies into medical training.

Published
2024
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4. Code Librarian: A Software Package Recommendation System

Author

Tao, Lili, Cazan, Alexandru-Petre, Ibraimoski, Senad, and Moran, Sean

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence
Abstract

The use of packaged libraries can significantly shorten the software development cycle by improving the quality and readability of code. In this paper, we present a recommendation engine called Librarian for open source libraries. A candidate library package is recommended for a given context if: 1) it has been frequently used with the imported libraries in the program; 2) it has similar functionality to the imported libraries in the program; 3) it has similar functionality to the developer's implementation, and 4) it can be used efficiently in the context of the provided code. We apply the state-of-the-art CodeBERT-based model for analysing the context of the source code to deliver relevant library recommendations to users.

Published
2022

5. List of contributors

Author

Aizawa, Shin-Ichi, primary, Alberdi, Pilar, additional, Alexander, David C., additional, Alía, Alberto, additional, Allison, D.G., additional, Amyes, Sebastian G.B., additional, An, Haoran, additional, Andrade, María J., additional, Antelmann, Haike, additional, Arias, Cesar A., additional, Asensio, Miguel A., additional, Axell-House, Dierdre B., additional, Bae, Hee-Won, additional, Baena, Laura Muñoz, additional, Baig, Abdul Mannan, additional, Bailey, Spenser O., additional, Baize, Sylvain, additional, Baldi, Pablo C., additional, Barbosa, Angela Silva, additional, Barbuddhe, Sukhadeo B., additional, Bard, Emilie, additional, Barry, Eileen M., additional, Basarab, Gregory S., additional, Beloborodova, N.V, additional, Bermúdez, Elena, additional, Bidmos, Fadil A., additional, Bisgaard, Magne, additional, Blakely, Garry W., additional, Bloch, Evan, additional, Boesen, Thias Oberg, additional, Bose, Dipayan, additional, Botero, Javier Enrique, additional, Bouabe, Hicham, additional, Bouchard, Michael J., additional, Bozue, Joel A., additional, Bradbury, Richard S., additional, Brett Moreau, G., additional, Cabezas-Cruz, Alejandro, additional, Cai, Rong-Jun, additional, Calderón, Enrique J., additional, Cao, Boyang, additional, Carmena, David, additional, Carvalho, Eneas, additional, Caulfield, Amanda D., additional, Cen, Shan, additional, Chai, Jong-Yil, additional, Chamberland, Robin R., additional, Champredon, David, additional, Chan, Edward D., additional, Charbon, Godefroid, additional, Chato, Connor, additional, Chelomina, G.N., additional, Chen, Jingyu, additional, Chen, Min, additional, Chen, Shuyu, additional, Chen, Suilin, additional, Chen, Yanfei, additional, Chen, Zhaoyuan, additional, Cheng, Aimin, additional, Cheng, Keding, additional, Chiu, Charles Y., additional, Cho, You-Hee, additional, Christensen, Henrik, additional, Chrtdernevskaya, E.A., additional, Contreras, Adolfo, additional, Contreras, Marinela, additional, Córdoba, Juan J., additional, Córdoba, María G., additional, Costa, Rita, additional, Cote, Christopher K., additional, Cui, Xiangling, additional, Cui, Yujun, additional, Dacal, Elena, additional, Dammann, Allison N., additional, Das, Shubhagata, additional, Dashti, Alejandro, additional, de la Fuente, José, additional, de la Garza, Mireya, additional, Delgado, Josué, additional, Delgado-Cuesta, Juan, additional, Deng, Haiteng, additional, Deng, Li, additional, Dey, Debajit, additional, Dhama, Kuldeep, additional, Diego, Juan García-Bernalt, additional, Ding, Hao, additional, Doern, Christopher D., additional, Dorman, Charles J., additional, Du, Zongmin, additional, Dunbar, Sherry A., additional, Duthie, Malcolm, additional, Dybvig, Kevin F., additional, Eakin, Ann E., additional, Eallonardo, Samuel J., additional, Eberly, Allison R., additional, Echeverry, Adriana Jaramillo, additional, Egland, Paul G., additional, El Zowalaty, Mohamed E., additional, Endsley, Janice Jones, additional, Eom, Keeseon S., additional, Evans, Benjamin A., additional, Falkinham, Joseph O., additional, Feng, Siwei, additional, Feng, Yaoyu, additional, Feng, Zongdi, additional, Fernández-Soto, Pedro, additional, Ferreira, Roux-Cil, additional, Flores-Huerta, Nadia, additional, Foster, Timothy J., additional, Fox-Moon, Sandra M., additional, Fraga, Tatiana Rodrigues, additional, Fredricks, David N., additional, Freitag, Nancy E., additional, Frimodt-Møller, Jakob, additional, Fuller, Risa, additional, Ganesh, Balasubramanian, additional, Gao, Ning, additional, García-Carnero, Laura C., additional, Garzetti, Debora, additional, Geoghegan, Joan A., additional, Ghenim, Raed, additional, Giambartolomei, Guillermo H., additional, Gilbert, Nicole M., additional, Gillis, Thomas Phillip, additional, Gladstone, Camilla A., additional, Gómez-Gaviria, Manuela, additional, Gómez-Marín, Jorge E., additional, Gong, Tengfang, additional, González, Ramón A., additional, Gray-Owen, Scott D., additional, Gu, Bing, additional, Guzmán-Téllez, Paula, additional, Hajal, Caroline, additional, Han, Yanping, additional, Hao, Yi, additional, Harrington, Amanda T., additional, Harris, Jason B., additional, Harvill, Eric T., additional, Hasan, S. Saif, additional, He, Guang-Jun, additional, He, Yongqun, additional, Heffron, Jared D., additional, Hidalgo, Paloma, additional, Hindiyeh, Musa Y., additional, Hreha, Teri N., additional, Hu, Xiaoyu, additional, Huang, Guanghua, additional, Huang, Jiangqing, additional, Huang, Liang, additional, Huang, Shifeng, additional, Huang, Xingxu, additional, Huang, Xueting, additional, Huang, Yilun, additional, Huffman, Anthony, additional, Humphreys, Tricia L., additional, Hunstad, David A., additional, Inglis, Timothy J.J., additional, Isaac, Lourdes, additional, Jacobs, Samantha E., additional, Janowicz, Diane M., additional, Jeon, Hyeong-Kyu, additional, Ji, Quanjiang, additional, Jia, Qi, additional, Jia, Wei, additional, Jin, Shouguang, additional, Jneidi, Lama, additional, Jose, Shinsmon, additional, Jung, Bong-Kwang, additional, Kattan, Randa, additional, Kaushik, Rahul, additional, Khare, Reeti, additional, Kim, Eun Sook, additional, Kirn, Thomas J., additional, Koo, Hyun, additional, Köster, Pamela C., additional, Krause, Peter J., additional, Kumar, Sanjai, additional, Kupz, Andreas, additional, Lambert, P.A., additional, Lamont, Richard J., additional, Langford, Paul R., additional, Lebeaux, David, additional, Legname, Giuseppe, additional, Li, Bin, additional, Li, Chunhao, additional, Li, Fen, additional, Li, Jun, additional, Li, Lanjuan, additional, Li, Ruofan, additional, Li, Ruoyu, additional, Li, Ting, additional, Li, Yang-Yang, additional, Li, Yanhua, additional, Li, Zhuorong, additional, Liang, Xiaomeng, additional, Liao, Guojian, additional, Lin, Ping, additional, Ling, Yun, additional, Liu, Bo, additional, Liu, Dongyou, additional, Liu, Guohua, additional, Liu, Huidi, additional, Liu, Jiafeng, additional, Liu, Jintao, additional, Liu, Qi, additional, Liu, Shu-Lin, additional, Liu, Taiping, additional, Liu, Tongbao, additional, Liu, Wei, additional, Liu, Yan, additional, Liu, Yanni, additional, Liu, Yisong, additional, Liu, Yuan, additional, Løbner-Olesen, Anders, additional, Loeffelholz, Michael, additional, Lu, Hongzhou, additional, Luna, Brian, additional, Ma, Bingting, additional, Ma, Chengying, additional, Ma, Shuang, additional, Ma, TianLi, additional, Madan, Rajat, additional, Mahle, Rachael E., additional, Mahlen, Steven D., additional, Malik, Satya Veer Singh, additional, Malik, Yashpal Singh, additional, Malvy, Denis, additional, Mann, Barbara J., additional, Marasini, Daya, additional, Maris, Alexander S., additional, Marjomäki, Varpu, additional, Marjuki, Henju, additional, Martín, Alberto, additional, Martín, Irene, additional, Martínez-Castillo, Moisés, additional, Martínez-Pabón, María Cecilia, additional, Mathison, Blaine A., additional, Ma’ayeh, Showgy, additional, McDowell, Andrew, additional, McLaughlin, Stephanie E., additional, McSheffrey, Gordon G., additional, Medrano, Francisco J., additional, Meehan, Conor J., additional, Mehta, Dhwani, additional, Mejía-Oquendo, Manuela, additional, Melo-Cristino, José, additional, Mendoza-Barberá, Elena, additional, Meng, Xinan, additional, Merino, Susana, additional, Merritt, Adam J., additional, Miller, Steve, additional, Miller, William R., additional, Minamino, Tohru, additional, Mirzaei, Mohammadali Khan, additional, Mora-Montes, Héctor M., additional, Mortensen, Joel, additional, Mostafa, Heba H., additional, Muhsen, Khitam, additional, Mujahed, Ahlam, additional, Muro, Antonio, additional, Murphy, Olwen C., additional, Newton, Hayley J., additional, Nguyen, April H., additional, Nichols, Wright W., additional, Niu, Siqiang, additional, Núñez, Félix, additional, Obregon, Dasiel, additional, Okamoto, Akira, additional, Okutani, Akiko, additional, Olabode, Abayomi, additional, Omar, Muna, additional, Ong, Edison, additional, Ouyang, Zhiming, additional, Pacak, Christina A., additional, Pacheco-Yépez, Judith, additional, Palmer, John, additional, Pang, Xiaoli, additional, Paredes-Sabja, Daniel, additional, Peng, Zhong, additional, Peng, Zonggen, additional, Pérez-Nevado, Francisco, additional, Poon, Art, additional, Pospíšilová, Petra, additional, Potts, Caelin C., additional, Pu, Qinqin, additional, Pujic, Petar, additional, Qi, Rui, additional, Qian, Chenyun, additional, Qian, Liu, additional, Qin, Aiping, additional, Qu, Fen, additional, Rakin, Alexander, additional, Ramesh, Ashwin, additional, Ramirez, Mario, additional, Rao, Yu, additional, Ratner, Adam J., additional, Rawool, Deepak B., additional, Rehman, Asma, additional, Ren, Jie, additional, Ren, Ping, additional, Retchless, Adam C., additional, Robertson, Erle S., additional, Rodríguez, Alicia, additional, Rodriguez, Azucena, additional, Rodríguez-Medina, Carolina, additional, Rodriguez-Nava, Veronica, additional, Rohde, Manfred, additional, Romero-Rodríguez, Alba, additional, Rosales-Morgan, Gabriela, additional, Rosenkranz, Andrea L., additional, Ruiz-Moyano, Santiago, additional, Ruokolainen, Visa, additional, Sabateen, Ali, additional, Sahu, Radhakrishna, additional, Sails, Andrew, additional, Sang, Yu, additional, Santana, Clarissa H., additional, Santos, Jesus A., additional, Santos, Renato L., additional, Schmitz, Jonathan E., additional, Serrano-Luna, Jesús, additional, Shen, Jianzhong, additional, Shen, Zhangqi, additional, Shibayama, Mineko, additional, Shirtliff, Mark E., additional, Silva-Costa, Catarina, additional, Silva-Olivares, Angélica, additional, Singh, Niraj Kumar, additional, Šmajs, David, additional, Smith, Robert P., additional, Smith, Sophie, additional, Snyder, Lori A.S., additional, Song, Yinggai, additional, Soro, Aurea Simon, additional, Spearman, Paul, additional, Spellberg, Brad, additional, Sprague, Lisa D., additional, Stratton, Charles W., additional, Strenk, Susan M., additional, Strugnell, Richard A., additional, Sun, Keer, additional, Suo, Xun, additional, Suzuki-Hatano, Silveli, additional, Svärd, Staffan, additional, Talbot, Elizabeth A., additional, Tamez-Castrellón, Alma K., additional, Tan, Nie, additional, Tang, Cynthia Y., additional, Tang, Yi-Wei, additional, Tao, Jia, additional, Tao, Lili, additional, Terrero-Salcedo, David, additional, Tharmalingam, Jayaraman, additional, Thwe, Phyu M., additional, Tiamani, Kawtar, additional, Tomás, Juan M., additional, Topaz, Nadav, additional, Tsai, Ang-Chen, additional, Tsalik, Ephraim L., additional, Tuomanen, Elaine I., additional, Turenne, Christine Y., additional, Tyagi, Anuj, additional, Uprety, Priyanka, additional, Valour, Florent, additional, van Hensbergen, Vincent P., additional, Venkatesan, Arun, additional, Vergis, Jess, additional, Villar, Margarita, additional, Vollmer, Waldemar, additional, Waites, Ken B., additional, Wan, Xiu-Feng, additional, Wang, Guiqing, additional, Wang, Lijun, additional, Wang, Lin, additional, Wang, Linqi, additional, Wang, Xiangru, additional, Wang, Xin, additional, Wang, Xinjie, additional, Wang, Ya-Ting, additional, Wang, Yang, additional, Wang, Yating, additional, Weil, Ana A., additional, Welkos, Susan L., additional, Wengenack, Nancy L., additional, Westblade, Lars F., additional, Whitfield, Chris, additional, Wu, Hui, additional, Wu, Lijuan, additional, Wu, Min, additional, Wu, Yarong, additional, Wu, Zhaowei, additional, Xiang, Ye, additional, Xiao, Di, additional, Xiao, Li, additional, Xiao, Lihua, additional, Xu, Tao, additional, Xu, Wenyue, additional, Xu, Xinping, additional, Xue, Jinling, additional, Yadav, Jay Prakash, additional, Yan, Junxiang, additional, Yan, Yixin, additional, Yang, Changmei, additional, Yang, Ruifu, additional, Yang, Ying, additional, Yao, Kaihu, additional, Yao, Yu-Feng, additional, Yeakle, Kyle C., additional, Yu, Demin, additional, Yu, Hao, additional, Yu, Xue-Jie, additional, Yuan, Zhenghong, additional, Zai, Wenjing, additional, Zhang, Jianzhong, additional, Zhang, Jing-Ren, additional, Zhang, Lanyue, additional, Zhang, Lijie, additional, Zhang, Qiwei, additional, Zhang, Wenbao, additional, Zhang, Wenhong, additional, Zhang, Xinxin, additional, Zhao, Youbao, additional, Zhou, Chuanmin, additional, Zhu, Feng, additional, Zhu, Jingting, additional, and Zhu, Yongqun, additional

Published
2024
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7. CV4Code: Sourcecode Understanding via Visual Code Representations

Author

Shi, Ruibo, Tao, Lili, Saphal, Rohan, Silavong, Fran, and Moran, Sean J.

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

We present CV4Code, a compact and effective computer vision method for sourcecode understanding. Our method leverages the contextual and the structural information available from the code snippet by treating each snippet as a two-dimensional image, which naturally encodes the context and retains the underlying structural information through an explicit spatial representation. To codify snippets as images, we propose an ASCII codepoint-based image representation that facilitates fast generation of sourcecode images and eliminates redundancy in the encoding that would arise from an RGB pixel representation. Furthermore, as sourcecode is treated as images, neither lexical analysis (tokenisation) nor syntax tree parsing is required, which makes the proposed method agnostic to any particular programming language and lightweight from the application pipeline point of view. CV4Code can even featurise syntactically incorrect code which is not possible from methods that depend on the Abstract Syntax Tree (AST). We demonstrate the effectiveness of CV4Code by learning Convolutional and Transformer networks to predict the functional task, i.e. the problem it solves, of the source code directly from its two-dimensional representation, and using an embedding from its latent space to derive a similarity score of two code snippets in a retrieval setup. Experimental results show that our approach achieves state-of-the-art performance in comparison to other methods with the same task and data configurations. For the first time we show the benefits of treating sourcecode understanding as a form of image processing task.

Published
2022

10. International Nosocomial Infection Control Consortium (INICC) report of health care associated infections, data summary of 45 countries for 2015 to 2020, adult and pediatric units, device-associated module

Author

Rosenthal, Victor D., Yin, Ruijie, Nercelles, Patricio, Rivera-Molina, Sara E., Jyoti, Somani, Dongol, Reshma, Aguilar-De-Moros, Daisy, Tumu, Nellie, Alarcon-Rua, Johana, Stagnaro, Juan P., Alkhawaja, Safaa, Jimenez-Alvarez, Luisa F., Cano-Medina, Yuliana A., Valderrama-Beltran, Sandra L., Henao-Rodas, Claudia M., Zuniga-Chavarria, Maria A., El-Kholy, Amani, Agha, Hala Mounir, Sahu, Suneeta, Anusandhan, Siksha O., Bhattacharyya, Mahuya, Kharbanda, Mohit, Poojary, Aruna, Nair, Pravin K., Myatra, Sheila N., Chawla, Rajesh, Sandhu, Kavita, Mehta, Yatin, Rajhans, Prasad, Zand, Farid, Abdellatif-Daboor, Mohammad, Tai, Chian-Wern, Gan, Chin S., Mat Nor, Mohd-Basri, Aguirre-Avalos, Guadalupe, Hernandez-Chena, Blanca E., Sassoe-Gonzalez, Alejandro, Villegas-Mota, Isabel, Aleman- Bocanegra, Mary C., Bat-Erdene, Ider, Carreazo, Nilton Y., Castaneda-Sabogal, Alex, Janc, Jarosław, Belskiy, Vladislav, Hlinkova, Sona, Yildizdas, Dincer, Havan, Merve, Koker, Alper, Sungurtekin, Hulya, Dinleyici, Ener C., Guclu, Ertugrul, Tao, Lili, Memish, Ziad A., and Jin, Zhilin

Published
2024
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12. Examining the impact of a 9-component bundle and the INICC multidimensional approach on catheter-associated urinary tract infection rates in 32 countries across Asia, Eastern Europe, Latin America, and the Middle East

Author

Rosenthal, Victor D., Yin, Ruijie, Jin, Zhilin, Perez, Valentina, Kis, Matthew A., Abdulaziz-Alkhawaja, Safaa, Valderrama-Beltran, Sandra L., Gomez, Katherine, Rodas, Claudia M.H., El-Sisi, Amal, Sahu, Suneeta, Kharbanda, Mohit, Rodrigues, Camilla, Myatra, Sheila N., Chawla, Rajesh, Sandhu, Kavita, Mehta, Yatin, Rajhans, Prasad, Arjun, Rajalakshmi, Tai, Chian-Wern, Bhakta, Arpita, Mat Nor, Mohd-Basri, Aguirre-Avalos, Guadalupe, Sassoe-Gonzalez, Alejandro, Bat-Erdene, Ider, Acharya, Subhash P., Aguilar-de-Moros, Daisy, Carreazo, Nilton Yhuri, Duszynska, Wieslawa, Hlinkova, Sona, Yildizdas, Dincer, Kılıc, Esra K., Dursun, Oguz, Odek, Caglar, Deniz, Suna S.O., Guclu, Ertugrul, Koksal, Iftihar, Medeiros, Eduardo A., Petrov, Michael M., Tao, Lili, Salgado, Estuardo, Dueñas, Lourdes, Daboor, Mohammad A., Raka, Lul, Omar, Abeer A., Ikram, Aamer, Horhat-Florin, George, Memish, Ziad A., and Brown, Eric C.

Published
2024
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15. Decreasing central line-associated bloodstream infections rates in intensive care units in 30 low- and middle-income countries: An INICC approach

Author

Rosenthal, Victor D., Jin, Zhilin, Brown, Eric C., Dongol, Reshma, De Moros, Daisy A., Alarcon-Rua, Johana, Perez, Valentina, Stagnaro, Juan P., Alkhawaja, Safaa, Jimenez-Alvarez, Luisa F., Cano-Medina, Yuliana A., Valderrama-Beltran, Sandra L., Henao-Rodas, Claudia M., Zuniga-Chavarria, Maria A., El-Kholy, Amani, Agha, Hala, Sahu, Suneeta, Mishra, Shakti B., Bhattacharyya, Mahuya, Kharbanda, Mohit, Poojary, Aruna, Nair, Pravin K., Myatra, Sheila N., Chawla, Rajesh, Sandhu, Kavita, Mehta, Yatin, Rajhans, Prasad, Abdellatif-Daboor, Mohammad, Chian-Wern, Tai, Gan, Chin Seng, Mohd-Basri, Mat Nor, Aguirre-Avalos, Guadalupe, Hernandez-Chena, Blanca E., Sassoe-Gonzalez, Alejandro, Villegas-Mota, Isabel, Aleman- Bocanegra, Mary C., Bat-Erdene, Ider, Carreazo, Nilton Y., Castaneda-Sabogal, Alex, Janc, Jarosław, Hlinkova, Sona, Yildizdas, Dincer, Havan, Merve, Koker, Alper, Sungurtekin, Hulya, Dinleyici, Ener C., Guclu, Ertugrul, Tao, Lili, Memish, Ziad A., and Yin, Ruijie

Published
2024
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16. Assessing the impact of a multidimensional approach and an 8-component bundle in reducing incidences of ventilator-associated pneumonia across 35 countries in Latin America, Asia, the Middle East, and Eastern Europe

Author

Rosenthal, Victor Daniel, Jin, Zhilin, Yin, Ruijie, Sahu, Suneeta, Rajhans, Prasad, Kharbanda, Mohit, Nair, Pravin K., Mishra, Shakti Bedanta, Chawla, Rajesh, Arjun, Rajalakshmi, Sandhu, Kavita, Rodrigues, Camilla, Dongol, Reshma, Myatra, Sheila Nainan, Mohd-Basri, Mat Nor, Chian-Wern, Tai, Bhakta, Arpita, Bat-Erdene, Ider, Acharya, Subhash P., Alvarez, Gustavo Andres, Moreno, Lina Alejandra Aguilar, Gomez, Katherine, da Jimenez-Alvarez, Luisa Fernanda, Henao-Rodas, Claudia Milena, Valderrama-Beltran, Sandra Liliana, Zuniga-Chavarria, Maria Adelia, Aguirre-Avalos, Guadalupe, Hernandez-Chena, Blanca Estela, Sassoe-Gonzalez, Alejandro, Aleman-Bocanegra, Mary Cruz, Villegas-Mota, Maria Isabel, De Moros, Daisy Aguilar, Castaneda-Sabogal, Alex, Carreazo, Nilton Yhuri, Alkhawaja, Safaa, Agha, Hala Mounir, El-Kholy, Amani, Abdellatif-Daboor, Mohammad, Dursun, Oguz, Okulu, Emel, Havan, Merve, Yildizdas, Dincer, Deniz, Suna Secil Ozturk, Guclu, Ertugrul, Hlinkova, Sona, Ikram, Aamer, Tao, Lili, Omar, Abeer Aly, Elahi, Naheed, Memish, Ziad A., Petrov, Michael M., Raka, Lul, Janc, Jarosław, Horhat-Florin, George, Medeiros, Eduardo Alexandrino, Salgado, Estuardo, Dueñas, Lourdes, Coloma, Monica, Perez, Valentina, and Brown, Eric Christopher

Published
2024
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17. CV4Code: Sourcecode Understanding via Visual Code Representations

Author

Shi, Ruibo, Tao, Lili, Saphal, Rohan, Silavong, Fran, Moran, Sean, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wang, Lei, editor, Gall, Juergen, editor, Chin, Tat-Jun, editor, Sato, Imari, editor, and Chellappa, Rama, editor

Published
2023
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19. An international prospective study of INICC analyzing the incidence and risk factors for catheter-associated urinary tract infections in 235 ICUs across 8 Asian Countries

Author

Rosenthal, Victor D., Yin, Ruijie, Abbo, Lilian M., Lee, Brandon H., Rodrigues, Camilla, Myatra, Sheila N., Divatia, Jigeeshu V., Kharbanda, Mohit, Nag, Bikas, Rajhans, Prasad, Shingte, Vasudha, Mehta, Yatin, Sarma, Smita, Todi, Subhash K., Bhattacharyya, Mahuya, Basu, Sushmita, Sahu, Suneeta, Mishra, Shakti B., Samal, Samir, Chawla, Rajesh, Jain, Aakanksha C., Nair, Pravin K., Kalapala, Durga, Arjun, Rajalakshmi, Singla, Deepak, Sandhu, Kavita, Badyal, Binesh, Palaniswamy, Vijayanand, Bhakta, Arpita, Gan, Chin S., Mohd-Basri, Mat N., Lai, Yin H., Tai, Chian-Wern, Lee, Pei-Chuen, Bat-Erdene, Ider, Begzjav, Tsolmon, Acharya, Subhash P., Dongol, Reshma, Ikram, Aamer, Tumu, Nellie, Tao, Lili, and Jin, Zhilin

Published
2024
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20. Towards Interpretable and Robust Hand Detection via Pixel-wise Prediction

Author

Liu, Dan, Zhang, Libo, Luo, Tiejian, Tao, Lili, and Wu, Yanjun

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The lack of interpretability of existing CNN-based hand detection methods makes it difficult to understand the rationale behind their predictions. In this paper, we propose a novel neural network model, which introduces interpretability into hand detection for the first time. The main improvements include: (1) Detect hands at pixel level to explain what pixels are the basis for its decision and improve transparency of the model. (2) The explainable Highlight Feature Fusion block highlights distinctive features among multiple layers and learns discriminative ones to gain robust performance. (3) We introduce a transparent representation, the rotation map, to learn rotation features instead of complex and non-transparent rotation and derotation layers. (4) Auxiliary supervision accelerates the training process, which saves more than 10 hours in our experiments. Experimental results on the VIVA and Oxford hand detection and tracking datasets show competitive accuracy of our method compared with state-of-the-art methods with higher speed., Comment: Accepted to Pattern Recognition

Published
2020
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22. Multinational prospective cohort study over 18 years of the risk factors for ventilator-associated pneumonia in 9 Asian countries: INICC findings

Author

Rosenthal, Victor Daniel, Yin, Ruijie, Rodrigues, Camilla, Myatra, Sheila Nainan, Divatia, Jigeeshu Vasishth, Biswas, Sanjay K, Shrivastava, Anjana Mahesh, Kharbanda, Mohit, Nag, Bikas, Mehta, Yatin, Sarma, Smita, Todi, Subhash Kumar, Bhattacharyya, Mahuya, Bhakta, Arpita, Gan, Chin Seng, Low, Michelle Siu Yee, Kushairi, Marissa Bt Madzlan, Chuah, Soo Lin, Wang, Qi Yuee, Chawla, Rajesh, Jain, Aakanksha Chawla, Kansal, Sudha, Bali, Roseleen Kaur, Arjun, Rajalakshmi, Davaadagva, Narangarav, Bat-Erdene, Batsuren, Begzjav, Tsolmon, Basri, Mat Nor Mohd, Tai, Chian-Wern, Lee, Pei-Chuen, Tang, Swee-Fong, Sandhu, Kavita, Badyal, Binesh, Arora, Ankush, Sengupta, Deep, Tao, Lili, and Jin, Zhilin

Published
2023
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31. Home Activity Monitoring using Low Resolution Infrared Sensor

Author

Tao, Lili, Volonakis, Timothy, Tan, Bo, Jing, Yanguo, Chetty, Kevin, and Smith, Melvyn

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Action monitoring in a home environment provides important information for health monitoring and may serve as input into a smart home environment. Visual analysis using cameras can recognise actions in a complex scene, such as someones living room. However, although there the huge potential benefits and importance, specifically for health, cameras are not widely accepted because of privacy concerns. This paper recognises human activities using a sensor that retains privacy. The sensor is not only different by being thermal, but it is also of low resolution: 8x8 pixels. The combination of the thermal imaging, and the low spatial resolution ensures the privacy of individuals. We present an approach to recognise daily activities using this sensor based on a discrete cosine transform. We evaluate the proposed method on a state-of-the-art dataset and experimentally confirm that our approach outperforms the baseline method. We also introduce a new dataset, and evaluate the method on it. Here we show that the sensor is considered better at detecting the occurrence of falls and Activities of Daily Living. Our method achieves an overall accuracy of 87.50% across 7 activities with a fall detection sensitivity of 100% and specificity of 99.21%.

Published
2018

34. Lenalidomide Treatment of Isolated Central Nervous System Relapse in Acute Lymphoblastic Leukemia after Hematopoietic Stem Cell Transplantation and Chimeric Antigen Receptor T-Cell Therapy.

Author

Zhang, Qing, Dong, Yi, Zhai, Zhimin, Tao, Lili, and Tao, Qianshan

Subjects
HEMATOPOIETIC stem cell transplantation, CHIMERIC antigen receptors, EXTRAMEDULLARY diseases, LYMPHOBLASTIC leukemia, HISTOCOMPATIBILITY antigens
Abstract

Introduction: Hematopoietic stem cell transplantation (HSCT) and chimeric antigen receptor T (CAR-T) cell are effective treatments for acute lymphoblastic leukemia (ALL). Various forms of intra- and extramedullary relapses have been reported after HSCT and CAR-T-cell therapy for ALL; however, no reports have investigated isolated central nervous system (CNS) relapse after HSCT and CAR-T-cell therapy. Hence, no clinical treatment has been established for such rare patients. Case Presentation: An 18-year-old male patient with B-cell ALL suffered from isolated CNS relapse after HSCT and CAR-T-cell therapy. Conventional systemic intravenous and intrathecal chemotherapies were ineffective and intolerable. A unique immunosuppressive microenvironment of decreasing NK cell percentage and increasing IL-8 concentration and CAR-T-cell exhaustion had been illustrated in the cerebrospinal fluid. Finally, the patient received immunomodulatory therapy with lenalidomide and obtained complete remission. Conclusion: Lenalidomide might be a therapeutic strategy for isolated CNS relapse after HSCT and CAR-T-cell therapy. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Reply to Kidd et al., “Inconsistencies within the proposed framework for stabilizing fungal nomenclature risk further confusion”

Author

de Hoog, Sybren, primary, Walsh, Thomas J., additional, Ahmed, Sarah A., additional, Alastruey-Izquierdo, Ana, additional, Alexander, Barbara D., additional, Arendrup, Maiken Cavling, additional, Babady, Esther, additional, Bai, Feng-Yan, additional, Balada-Llasat, Joan-Miquel, additional, Borman, Andrew, additional, Chowdhary, Anuradha, additional, Clark, Andrew, additional, Colgrove, Robert C., additional, Cornely, Oliver A., additional, Dingle, Tanis C., additional, Dufresne, Philippe J., additional, Fuller, Jeff, additional, Gangneux, Jean-Pierre, additional, Gibas, Connie, additional, Glasgow, Heather, additional, Graser, Yvonne, additional, Guillot, Jacques, additional, Groll, Andreas H., additional, Haase, Gerhard, additional, Hanson, Kimberly, additional, Harrington, Amanda, additional, Hawksworth, David L., additional, Hayden, Randall T., additional, Hoenigl, Martin, additional, Hubka, Vit, additional, Johnson, Kristie, additional, Kus, Julianne V., additional, Li, Ruoyu, additional, Meis, Jacques F., additional, Lackner, Michaela, additional, Lanternier, Fanny, additional, Leal, Sixto M., additional, Lee, Francesca, additional, Lockhart, Shawn R., additional, Luethy, Paul, additional, Martin, Isabella, additional, Kwon-Chung, Kyung J., additional, Meyer, Wieland, additional, Nguyen, M. Hong, additional, Ostrosky-Zeichner, Luis, additional, Palavecino, Elizabeth, additional, Pancholi, Preeti, additional, Pappas, Peter G., additional, Procop, Gary W., additional, Redhead, Scott A., additional, Rhoads, Daniel D., additional, Riedel, Stefan, additional, Stevens, Bryan, additional, Sullivan, Kaede Ota, additional, Vergidis, Paschalis, additional, Roilides, Emmanuel, additional, Seyedmousavi, Amir, additional, Tao, Lili, additional, Vicente, Vania A., additional, Vitale, Roxana G., additional, Wang, Qi-Ming, additional, Wengenack, Nancy L., additional, Westblade, Lars, additional, Wiederhold, Nathan, additional, White, Lewis, additional, Wojewoda, Christina M., additional, and Zhang, Sean X., additional

Published
2024
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39. A multi-species outbreak of VIM-producing carbapenem-resistant bacteria in a burn unit and subsequent investigation of rapid development of cefiderocol resistance

Author

Freiberg, Jeffrey A., primary, Tao, Lili, additional, Manuel, Carmila, additional, Mike, Laura A., additional, Nelson, George E., additional, Harris, Bryan D., additional, Mathers, Amy J., additional, Talbot, Thomas R., additional, Skaar, Eric P., additional, and Humphries, Romney M., additional

Published
2024
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41. Evaluating the outcome of a bundle with 11 components and the INICC multidimensional approach in decreasing rates of central line-associated bloodstream infections across nine Asian countries

Author

Rosenthal, Victor Daniel, primary, Yin, Ruijie, additional, Myatra, Sheila Nainan, additional, Divatia, Jigeeshu Vasishth, additional, Biswas, Sanjay K, additional, Shrivastava, Anjana Mahesh, additional, Perez, Valentina, additional, Wang, Qi Yuee, additional, Todi, Subhash Kumar, additional, Tang, Swee Fong, additional, Tai, Chian Wern, additional, Lee, Pei-Chuen, additional, Sengupta, Deep, additional, Sarma, Smita, additional, Sandhu, Kavita, additional, Rodrigues, Camilla, additional, Nag, Bikas, additional, Mohd-Basri, Mat Nor, additional, Mehta, Yatin, additional, Kharbanda, Mohit, additional, Kansal, Sudha, additional, Jain, Aakanksha Chawla, additional, Davaadagva, Narangarav, additional, Chuah, Soo Lin, additional, Low, Michelle Siu Yee, additional, Gan, Chin Seng, additional, Bt Madzlan Kushairi, Marissa, additional, Bhattacharyya, Mahuya, additional, Bhakta, Arpita, additional, Begzjav, Tsolmon, additional, Bat-Erdene, Batsuren, additional, Bali, Roseleen Kaur, additional, Badyal, Binesh, additional, Arora, Ankush, additional, Arjun, Rajalakshmi, additional, Tao, Lili, additional, Jin, Zhilin, additional, and Chawla, Rajesh, additional

Published
2024
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44. Calorie Counter: RGB-Depth Visual Estimation of Energy Expenditure at Home

Author

Tao, Lili, Burghardt, Tilo, Mirmehdi, Majid, Damen, Dima, Cooper, Ashley, Hannuna, Sion, Camplani, Massimo, Paiement, Adeline, and Craddock, Ian

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We present a new framework for vision-based estimation of calorific expenditure from RGB-D data - the first that is validated on physical gas exchange measurements and applied to daily living scenarios. Deriving a person's energy expenditure from sensors is an important tool in tracking physical activity levels for health and lifestyle monitoring. Most existing methods use metabolic lookup tables (METs) for a manual estimate or systems with inertial sensors which ultimately require users to wear devices. In contrast, the proposed pose-invariant and individual-independent vision framework allows for a remote estimation of calorific expenditure. We introduce, and evaluate our approach on, a new dataset called SPHERE-calorie, for which visual estimates can be compared against simultaneously obtained, indirect calorimetry measures based on gas exchange. % based on per breath gas exchange. We conclude from our experiments that the proposed vision pipeline is suitable for home monitoring in a controlled environment, with calorific expenditure estimates above accuracy levels of commonly used manual estimations via METs. With the dataset released, our work establishes a baseline for future research for this little-explored area of computer vision.

Published
2016

45. Multiple Human Tracking in RGB-D Data: A Survey

Author

Camplani, Massimo, Paiement, Adeline, Mirmehdi, Majid, Damen, Dima, Hannuna, Sion, Burghardt, Tilo, and Tao, Lili

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Multiple human tracking (MHT) is a fundamental task in many computer vision applications. Appearance-based approaches, primarily formulated on RGB data, are constrained and affected by problems arising from occlusions and/or illumination variations. In recent years, the arrival of cheap RGB-Depth (RGB-D) devices has {led} to many new approaches to MHT, and many of these integrate color and depth cues to improve each and every stage of the process. In this survey, we present the common processing pipeline of these methods and review their methodology based (a) on how they implement this pipeline and (b) on what role depth plays within each stage of it. We identify and introduce existing, publicly available, benchmark datasets and software resources that fuse color and depth data for MHT. Finally, we present a brief comparative evaluation of the performance of those works that have applied their methods to these datasets.

Published
2016

47. Multinational prospective cohort study of incidence and risk factors for central line-associated bloodstream infections over 18 years in 281 ICUs of 9 Asian countries

Author

Rosenthal, Victor Daniel, Yin, Ruijie, Rodrigues, Camilla, Myatra, Sheila Nainan, Divatia, Jigeeshu Vasishth, Biswas, Sanjay K, Shrivastava, Anjana Mahesh, Kharbanda, Mohit, Nag, Bikas, Mehta, Yatin, Sarma, Smita, Todi, Subhash Kumar, Bhattacharyya, Mahuya, Bhakta, Arpita, Gan, Chin Seng, Low, Michelle Siu Yee, Bt Madzlan Kushairi, Marissa, Chuah, Soo Lin, Wang, Qi Yuee, Chawla, Rajesh, Jain, Aakanksha Chawla, Kansal, Sudha, Bali, Roseleen Kaur, Arjun, Rajalakshmi, Davaadagva, Narangarav, Bat-Erdene, Ider, Begzjav, Tsolmon, Mohd Basri, Mat Nor, Tai, Chian-Wern, Lee, Pei-Chuen, Tang, Swee-Fong, Sandhu, Kavita, Badyal, Binesh, Arora, Ankush, Sengupta, Deep, Tao, Lili, and Jin, Zhilin

Abstract

Background: Our objective was to identify central line (CL)-associated bloodstream infections (CLABSI) rates and risk factors (RF) in Asia.Methods: From 03/27/2004 to 02/11/2022, we conducted a multinational multicenter prospective cohort study in 281 ICUs of 95 hospitals in 44 cities in 9 Asian countries (China, India, Malaysia, Mongolia, Nepal, Pakistan, Philippines, Sri Lanka, Thailand, and Vietnam). For estimation of CLABSI rate we used CL-days as denominator and number of CLABSI as numerator. To estimate CLABSI RF for we analyzed the data using multiple logistic regression, and outcomes are shown as adjusted odds ratios (aOR).Results: A total of 150,142 patients, hospitalized 853,604 days, acquired 1514 CLABSIs. Pooled CLABSI rate per 1000 CL-days was 5.08; per type of catheter were: femoral: 6.23; temporary hemodialysis: 4.08; jugular: 4.01; arterial: 3.14; PICC: 2.47; subclavian: 2.02. The highest rates were femoral, temporary for hemodialysis, and jugular, and the lowest PICC and subclavian. We analyzed following variables: Gender, age, length of stay (LOS) before CLABSI acquisition, CL-days before CLABSI acquisition, CL-device utilization ratio, CL-type, tracheostomy use, hospitalization type, ICU type, facility ownership and World Bank classifications by income level. Following were independently associated with CLABSI: LOS before CLABSI acquisition, rising risk 4% daily (aOR = 1.04; 95% CI = 1.03–1.04; p< 0.0001); number of CL-days before CLABSI acquisition, rising risk 5% per CL-day (aOR = 1.05; 95% CI 1.05–1.06; p< 0.0001); medical hospitalization (aOR = 1.21; 95% CI 1.04–1.39; p= 0.01); tracheostomy use (aOR = 2.02;95% CI 1.43–2.86; p< 0.0001); publicly-owned facility (aOR = 3.63; 95% CI 2.54–5.18; p< 0.0001); lower-middle-income country (aOR = 1.87; 95% CI 1.41–2.47; p< 0.0001). ICU with highest risk was pediatric (aOR = 2.86; 95% CI 1.71–4.82; p< 0.0001), followed by medical-surgical (aOR = 2.46; 95% CI 1.62–3.75; p< 0.0001). CL with the highest risk were internal-jugular (aOR = 3.32; 95% CI 2.84–3.88; p< 0.0001), and femoral (aOR = 3.13; 95% CI 2.48–3.95; p< 0.0001), and subclavian (aOR = 1.78; 95% CI 1.47–2.15; p< 0.0001) showed the lowest risk.Conclusions: The following CLABSI RFs are unlikely to change: country income level, facility-ownership, hospitalization type, and ICU type. Based on these findings it is suggested to focus on reducing LOS, CL-days, and tracheostomy; using subclavian or PICC instead of internal-jugular or femoral; and implementing evidence-based CLABSI prevention recommendations.

Published
2024
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48. Incidence and risk factors for catheter-associated urinary tract infection in 623 intensive care units throughout 37 Asian, African, Eastern European, Latin American, and Middle Eastern nations: A multinational prospective research of INICC

Author

Rosenthal, Victor Daniel, Yin, Ruijie, Brown, Eric Christopher, Lee, Brandon Hochahn, Rodrigues, Camilla, Myatra, Sheila Nainan, Kharbanda, Mohit, Rajhans, Prasad, Mehta, Yatin, Todi, Subhash Kumar, Basu, Sushmita, Sahu, Suneeta, Mishra, Shakti Bedanta, Chawla, Rajesh, Nair, Pravin K., Arjun, Rajalakshmi, Singla, Deepak, Sandhu, Kavita, Palaniswamy, Vijayanand, Bhakta, Arpita, Nor, Mohd Basri Mat, Chian-Wern, Tai, Bat-Erdene, Ider, Acharya, Subhash P., Ikram, Aamer, Tumu, Nellie, Tao, Lili, Alvarez, Gustavo Andres, Valderrama-Beltran, Sandra Liliana, Jiménez-Alvarez, Luisa Fernanda, Henao-Rodas, Claudia Milena, Gomez, Katherine, Aguilar-Moreno, Lina Alejandra, Cano-Medina, Yuliana Andrea, Zuniga-Chavarria, Maria Adelia, Aguirre-Avalos, Guadalupe, Sassoe-Gonzalez, Alejandro, Aleman-Bocanegra, Mary Cruz, Hernandez-Chena, Blanca Estela, Villegas-Mota, Maria Isabel, Aguilar-De-Moros, Daisy, Castañeda-Sabogal, Alex, Medeiros, Eduardo Alexandrino, Dueñas, Lourdes, Carreazo, Nilton Yhuri, Salgado, Estuardo, Abdulaziz-Alkhawaja, Safaa, Agha, Hala Mounir, El-Kholy, Amani Ali, Daboor, Mohammad Abdellatif, Guclu, Ertugrul, Dursun, Oguz, Koksal, Iftihar, Havan, Merve, Ozturk-Deniz, Suna Secil, Yildizdas, Dincer, Okulu, Emel, Omar, Abeer Aly, Memish, Ziad A., Janc, Jarosław, Hlinkova, Sona, Duszynska, Wieslawa, Horhat-Florin, George, Raka, Lul, Petrov, Michael M., Jin, Zhilin, Rosenthal, Victor Daniel, Yin, Ruijie, Brown, Eric Christopher, Lee, Brandon Hochahn, Rodrigues, Camilla, Myatra, Sheila Nainan, Kharbanda, Mohit, Rajhans, Prasad, Mehta, Yatin, Todi, Subhash Kumar, Basu, Sushmita, Sahu, Suneeta, Mishra, Shakti Bedanta, Chawla, Rajesh, Nair, Pravin K., Arjun, Rajalakshmi, Singla, Deepak, Sandhu, Kavita, Palaniswamy, Vijayanand, Bhakta, Arpita, Nor, Mohd Basri Mat, Chian-Wern, Tai, Bat-Erdene, Ider, Acharya, Subhash P., Ikram, Aamer, Tumu, Nellie, Tao, Lili, Alvarez, Gustavo Andres, Valderrama-Beltran, Sandra Liliana, Jiménez-Alvarez, Luisa Fernanda, Henao-Rodas, Claudia Milena, Gomez, Katherine, Aguilar-Moreno, Lina Alejandra, Cano-Medina, Yuliana Andrea, Zuniga-Chavarria, Maria Adelia, Aguirre-Avalos, Guadalupe, Sassoe-Gonzalez, Alejandro, Aleman-Bocanegra, Mary Cruz, Hernandez-Chena, Blanca Estela, Villegas-Mota, Maria Isabel, Aguilar-De-Moros, Daisy, Castañeda-Sabogal, Alex, Medeiros, Eduardo Alexandrino, Dueñas, Lourdes, Carreazo, Nilton Yhuri, Salgado, Estuardo, Abdulaziz-Alkhawaja, Safaa, Agha, Hala Mounir, El-Kholy, Amani Ali, Daboor, Mohammad Abdellatif, Guclu, Ertugrul, Dursun, Oguz, Koksal, Iftihar, Havan, Merve, Ozturk-Deniz, Suna Secil, Yildizdas, Dincer, Okulu, Emel, Omar, Abeer Aly, Memish, Ziad A., Janc, Jarosław, Hlinkova, Sona, Duszynska, Wieslawa, Horhat-Florin, George, Raka, Lul, Petrov, Michael M., and Jin, Zhilin

Abstract

Objective: To identify urinary catheter (UC)-associated urinary tract infection (CAUTI) incidence and risk factors. Design: A prospective cohort study. Setting: The study was conducted across 623 ICUs of 224 hospitals in 114 cities in 37 African, Asian, Eastern European, Latin American, and Middle Eastern countries. Participants: The study included 169,036 patients, hospitalized for 1,166,593 patient days. Methods: Data collection took place from January 1, 2014, to February 12, 2022. We identified CAUTI rates per 1,000 UC days and UC device utilization (DU) ratios stratified by country, by ICU type, by facility ownership type, by World Bank country classification by income level, and by UC type. To estimate CAUTI risk factors, we analyzed 11 variables using multiple logistic regression. Results: Participant patients acquired 2,010 CAUTIs. The pooled CAUTI rate was 2.83 per 1,000 UC days. The highest CAUTI rate was associated with the use of suprapubic catheters (3.93 CAUTIs per 1,000 UC days); with patients hospitalized in Eastern Europe (14.03) and in Asia (6.28); with patients hospitalized in trauma (7.97), neurologic (6.28), and neurosurgical ICUs (4.95); with patients hospitalized in lower-middle-income countries (3.05); and with patients in public hospitals (5.89). The following variables were independently associated with CAUTI: Age (adjusted odds ratio [aOR], 1.01; P <.0001), female sex (aOR, 1.39; P <.0001), length of stay (LOS) before CAUTI-acquisition (aOR, 1.05; P <.0001), UC DU ratio (aOR, 1.09; P <.0001), public facilities (aOR, 2.24; P <.0001), and neurologic ICUs (aOR, 11.49; P <.0001). Conclusions: CAUTI rates are higher in patients with suprapubic catheters, in middle-income countries, in public hospitals, in trauma and neurologic ICUs, and in Eastern European and Asian facilities. Based on findings regarding risk factors for CAUTI, focus on reducing LOS and UC utilization is warranted, as well as implementing evidence-based CAUTI-prevention recomm

Published
2024

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