Geospatial Monitoring of Body Mass Index : Use of Electronic Health Record Data Across Health Care Systems

Autor: Anthamatten, Peter, Thomas, Deborah S.K., Williford, Devon, Barrow, Jennifer C., Bol, Kirk A., Davidson, Arthur J., Davies, Sara J. Deakyne, Kraus, Emily McCormick, Tabano, David C., Daley, Matthew F.

Publikováno v: Public Health Reports (1974-), 2020 Mar 01. 135(2), 211-219.

Externí odkaz: https://www.jstor.org/stable/26990687

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Characterizing Patient Representations for Computational Phenotyping

Autor: Tiffany J. Callahan, Adrianne L. Stefanksi, Danielle M. Ostendorf, Jordan M. Wyrwa, Sara J. Deakyne Davies, George Hripcsak, Lawrence E. Hunter, Michael G. Kahn

Publikováno v: AMIA Annu Symp Proc

Patient representation learning methods create rich representations of complex data and have potential to further advance the development of computational phenotypes (CP). Currently, these methods are either applied to small predefined concept sets o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e212110752ced04d0f73fd182ef99796
https://europepmc.org/articles/PMC10148332/

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Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative

Autor: Emily R, Pfaff, Andrew T, Girvin, Davera L, Gabriel, Kristin, Kostka, Michele, Morris, Matvey B, Palchuk, Harold P, Lehmann, Benjamin, Amor, Mark, Bissell, Katie R, Bradwell, Sigfried, Gold, Stephanie S, Hong, Johanna, Loomba, Amin, Manna, Julie A, McMurry, Emily, Niehaus, Nabeel, Qureshi, Anita, Walden, Xiaohan Tanner, Zhang, Richard L, Zhu, Richard A, Moffitt, Melissa A, Haendel, Christopher G, Chute, William G, Adams, Shaymaa, Al-Shukri, Alfred, Anzalone, Ahmad, Baghal, Tellen D, Bennett, Elmer V, Bernstam, Mark M, Bissell, Brian, Bush, Thomas R, Campion, Victor, Castro, Jack, Chang, Deepa D, Chaudhari, Wenjin, Chen, San, Chu, James J, Cimino, Keith A, Crandall, Mark, Crooks, Sara J Deakyne, Davies, John, DiPalazzo, David, Dorr, Dan, Eckrich, Sarah E, Eltinge, Daniel G, Fort, George, Golovko, Snehil, Gupta, Janos G, Hajagos, David A, Hanauer, Brett M, Harnett, Ronald, Horswell, Nancy, Huang, Steven G, Johnson, Michael, Kahn, Kamil, Khanipov, Curtis, Kieler, Katherine Ruiz De, Luzuriaga, Sarah, Maidlow, Ashley, Martinez, Jomol, Mathew, James C, McClay, Gabriel, McMahan, Brian, Melancon, Stephane, Meystre, Lucio, Miele, Hiroki, Morizono, Ray, Pablo, Lav, Patel, Jimmy, Phuong, Daniel J, Popham, Claudia, Pulgarin, Carlos, Santos, Indra Neil, Sarkar, Nancy, Sazo, Soko, Setoguchi, Selvin, Soby, Sirisha, Surampalli, Christine, Suver, Uma Maheswara Reddy, Vangala, Shyam, Visweswaran, James von, Oehsen, Kellie M, Walters, Laura, Wiley, David A, Williams, Adrian, Zai

Publikováno v: Journal of the American Medical Informatics Association : JAMIA

Objective In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3533d16eaddda730bcfae1d98babd62d
https://ora.ox.ac.uk/objects/uuid:b846d295-7fb7-4e4f-b878-2edbdca8fe09