Quantifying association and disparities between diabetes complications and COVID-19 outcomes: A retrospective study using electronic health records von Paramita, Ni Luh Putu S. P, Agor, Joseph K, Mayorga, Maria E, Ivy, Julie S, Miller, Kristen E, Ozaltin, Osman Y

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Models for predicting the evolution of influenza to inform vaccine strain selection von Agor, Joseph K., Özaltın, Osman Y.

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Septic shock prediction and knowledge discovery through temporal pattern mining von Agor, Joseph K., Li, Ruoting, Özaltın, Osman Y.

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Prediction of Sepsis Related Mortality: An Optimization Approach von Agor, Joseph K., Paramita, Ni Luh Putu S. P., Ozaltn, Osman Y.

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Getting to the Heart of the Matter: A Triage Model to Improve Utilization of Cardiology Consultative Services von Agor, Joseph K., Sir, Mustafa Y., Pasupathy, Kalyan S., Foley, David A., Scott, Christopher G., Elrashidi, Muhamad Y., Young, Nathan P., McKie, Paul M.

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Temporal pattern mining for knowledge discovery in the early prediction of septic shock von Li, Ruoting, Agor, Joseph K., Özaltın, Osman Y.

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Feature selection for classification models via bilevel optimization von Agor, Joseph, Özaltın, Osman Y.

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Objective measures of workload in healthcare: a narrative review von Fishbein, Daniela, Nambiar, Siddhartha, McKenzie, Kendall, Mayorga, Maria, Miller, Kristen, Tran, Kevin, Schubel, Laura, Agor, Joseph, Kim, Tracy, Capan, Muge

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The value of missing information in severity of illness score development von Agor, Joseph, Özaltın, Osman Y., Ivy, Julie S., Capan, Muge, Arnold, Ryan, Romero, Santiago

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Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort Collaborative von Loomba, Johanna, Pfaff, Emily, Mitchell, Elliot, Delong, Grant, Tariq, Adbul, Coyle, Jeremy, Mertens, Andrew, Hubbard, Alan, Gao, Jifan, Li, Ziyang, Holmes, John, Wong, Eric, Getzen, Emily, Al-Amery, Amera, Anand, Adit, Baghbanzadeh, Mahdi, Bangert, Bridget, Butzin-Dozier, Zachary, Chiang, Jeffrey, Dai, Zongyu, Deng, Kaiwen, Dinh, Dong, Fu, Sunyang, Gardner, Kelly, Ghalwash, Mohamed, Ham, Colby, Hanoudi, Samer, Hershkovich, Leeor, Huang, Jiani, Huang, Yu, Hur, Junguk, Ismail, Hamid, Izmirlian, Grant, Jang, Kuk, Kartoun, Uri, Krichevsky, Spencer, Larie, Dale, Lederer, Lauren, Liu, Feifan, Munia, Tamanna, Madhira, Vithal, Mansourifard, Farzaneh, Milo, Christopher, Musal, Rasim, Narain, Rohan, Peng, Le, Perkins, Diana, Poplavskiy, Dmytro, Pungitore, Sarah, Ravichandran, Sarangan, Reyes, Abel, Rouffa, Sean, Sawant, Sahil, Schiaffino, Melody, Sengupta, Saurav, Shalaev, Ruslan, Shi, Seraphina, Shinguyen, Linh, Strube, Jan, Sundararajan, Prathic, Tawiah, Edward, Walzer, Benjamin, Wang, Lu, Wu, Yifeng, Xia, Fangfang, Yin, Changyu, Zanaj, Martin, Zhao, Zixuan, Zhou, Andrea, Zhu, Yuanda, Bates, Benjamin, Beasley, Will, Bramante, Carolyn, Brown, Don, Burgoon, Penny, Buse, John, Fuentes, Rafael, Gabriel, Davera, Gagnier, Joel, Gersing, Kenneth, Girvin, Andrew, Hurley, Robert, Johnson, Steve, Koraishy, Farrukh, Kostka, Kristin, Mariona, Federico, Marti, Emily, Martin, Greg, Mehta, Hemalkumar, Miller, Robert, Northington, Lavance, O’Neil, Shawn, Patel, Brijesh, Patel, Rena, Portilla, Lili, Sokos, George, Suver, Christine, Walden, Anita, Walters, Kellie, Zhu, Richard

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Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort CollaborativeResearch in context von Timothy Bergquist, Johanna Loomba, Emily Pfaff, Fangfang Xia, Zixuan Zhao, Yitan Zhu, Elliot Mitchell, Biplab Bhattacharya, Gaurav Shetty, Tamanna Munia, Grant Delong, Adbul Tariq, Zachary Butzin-Dozier, Yunwen Ji, Haodong Li, Jeremy Coyle, Seraphina Shi, Rachael V. Philips, Andrew Mertens, Romain Pirracchio, Mark van der Laan, John M. Colford, Jr, Alan Hubbard, Jifan Gao, Guanhua Chen, Neelay Velingker, Ziyang Li, Yinjun Wu, Adam Stein, Jiani Huang, Zongyu Dai, Qi Long, Mayur Naik, John Holmes, Danielle Mowery, Eric Wong, Ravi Parekh, Emily Getzen, Jake Hightower, Jennifer Blase, Ataes Aggarwal, Joseph Agor, Amera Al-Amery, Oluwatobiloba Aminu, Adit Anand, Corneliu Antonescu, Mehak Arora, Sayed Asaduzzaman, Tanner Asmussen, Mahdi Baghbanzadeh, Frazier Baker, Bridget Bangert, Laila Bekhet, Biplab Bhattacharya, Jenny Blase, Zachary Butzin-Dozier, Brian Caffo, Hao Chang, Zeyuan Chen, Jiandong Chen, Jeffrey Chiang, Peter Cho, Robert Cockrell, Parker Combs, Jeremy Coyle, Ciara Crosby, Zongyu Dai, Ran Dai, Anseh Danesharasteh, Elif Yildirim, Grant Delong, Ryan Demilt, Kaiwen Deng, Sanjoy Dey, Rohan Dhamdhere, Andrew Dickson, Phoebe Dijour, Dong Dinh, Richard Dixon, Albi Domi, Souradeep Dutta, Mirna Elizondo, Zeynep Ertem, Solomon Feuerwerker, Danica Fliss, Jennifer Fowler, Sunyang Fu, Kelly Gardner, Neil Getty, Mohamed Ghalwash, Logan Gloster, Phil Greer, Yuanfang Guan, Colby Ham, Samer Hanoudi, Jeremy Harper, Nathaniel Hendrix, Leeor Hershkovich, Jake Hightower, Junjie Hu

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Multi-Objective Optimization-Based Anonymization of Structured Data for Machine Learning von Wei, Yusi, Benson, Hande Y, Agor, Joseph K, Capan, Muge

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Quantifying association and disparities between diabetes complications and COVID-19 outcomes: A retrospective study using electronic health records von Ni Luh Putu S P Paramita, Joseph K Agor, Maria E Mayorga, Julie S Ivy, Kristen E Miller, Osman Y Ozaltin

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THE BOOTLEG COAL INDUSTRY von Agor, Joseph

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Anthropogenic Renourishment Feedback on Shorebirds: a Multispecies Bayesian Perspective von Convertino, Matteo, Donoghue, Joseph, Chu-Agor, Ma Librada, Kiker, Gregory, Munoz-Carpena, Rafael, Fischer, Richard, Linkov, Igor

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