Results 61 to 70 of about 2,261 (201)

Detecting and Filtering Immune-Related Adverse Events Signal Based on Text Mining and Observational Health Data Sciences and Informatics Common Data Model: Framework Development Study

JMIR Medical Informatics, 2020
BackgroundImmune checkpoint inhibitors are associated with unique immune-related adverse events (irAEs). As most of the immune checkpoint inhibitors are new to the market, it is important to conduct studies using real-world data sources to investigate ...
Yu, Yue, Ruddy, Kathryn, Mansfield, Aaron, Zong, Nansu, Wen, Andrew, Tsuji, Shintaro, Huang, Ming, Liu, Hongfang, Shah, Nilay, Jiang, Guoqian   +9 more
doaj   +1 more source

Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Clinical Epidemiology, 2022
Kristin Kostka,1,2 Talita Duarte-Salles,3 Albert Prats-Uribe,4 Anthony G Sena,5,6 Andrea Pistillo,3 Sara Khalid,4 Lana YH Lai,7 Asieh Golozar,8,9 Thamir M Alshammari,10 Dalia M Dawoud,11 Fredrik Nyberg,12 Adam B Wilcox,13,14 Alan Andryc,5 Andrew Williams,
Kostka K, Duarte-Salles T, Prats-Uribe A, Sena AG, Pistillo A, Khalid S, Lai LYH, Golozar A, Alshammari TM, Dawoud DM, Nyberg F, Wilcox AB, Andryc A, Williams A, Ostropolets A, Areia C, Jung CY, Harle CA, Reich CG, Blacketer C, Morales DR, Dorr DA, Burn E, Roel E, Tan EH, Minty E, DeFalco F, de Maeztu G, Lipori G, Alghoul H, Zhu H, Thomas JA, Bian J, Park J, Martínez Roldán J, Posada JD, Banda JM, Horcajada JP, Kohler J, Shah K, Natarajan K, Lynch KE, Liu L, Schilling LM, Recalde M, Spotnitz M, Gong M, Matheny ME, Valveny N, Weiskopf NG, Shah N, Alser O, Casajust P, Park RW, Schuff R, Seager S, DuVall SL, You SC, Song S, Fernández-Bertolín S, Fortin S, Magoc T, Falconer T, Subbian V, Huser V, Ahmed WUR, Carter W, Guan Y, Galvan Y, He X, Rijnbeek PR, Hripcsak G, Ryan PB, Suchard MA, Prieto-Alhambra D   +74 more
doaj  

OHDSI/PhenotypeLibrary: Release v3.28.1

, 2023
<p>See NEWS.md for release notes.</p ...
Gowtham Rao
core   +1 more source

Assessing the Use of German Claims Data Vocabularies for Research in the Observational Medical Outcomes Partnership Common Data Model: Development and Evaluation Study

JMIR Medical Informatics, 2023
BackgroundNational classifications and terminologies already routinely used for documentation within patient care settings enable the unambiguous representation of clinical information.
Elisa Henke, Michéle Zoch, Michael Kallfelz, Thomas Ruhnke, Liz Annika Leutner, Melissa Spoden, Christian Günster, Martin Sedlmayr, Franziska Bathelt   +8 more
doaj   +1 more source

OHDSI/PhenotypeLibrary: Release v3.21.0

, 2023
<p>See NEWS.md for release notes.</p ...
Gowtham Rao
core   +1 more source

Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study

JMIR Medical Informatics, 2021
BackgroundSARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not.
Reps, Jenna M, Kim, Chungsoo, Williams, Ross D, Markus, Aniek F, Yang, Cynthia, Duarte-Salles, Talita, Falconer, Thomas, Jonnagaddala, Jitendra, Williams, Andrew, Fernández-Bertolín, Sergio, DuVall, Scott L, Kostka, Kristin, Rao, Gowtham, Shoaibi, Azza, Ostropolets, Anna, Spotnitz, Matthew E, Zhang, Lin, Casajust, Paula, Steyerberg, Ewout W, Nyberg, Fredrik, Kaas-Hansen, Benjamin Skov, Choi, Young Hwa, Morales, Daniel, Liaw, Siaw-Teng, Abrahão, Maria Tereza Fernandes, Areia, Carlos, Matheny, Michael E, Lynch, Kristine E, Aragón, María, Park, Rae Woong, Hripcsak, George, Reich, Christian G, Suchard, Marc A, You, Seng Chan, Ryan, Patrick B, Prieto-Alhambra, Daniel, Rijnbeek, Peter R   +36 more
doaj   +1 more source

Implementation of inclusion and exclusion criteria of clinical studies in the software OHDSI ATLAS

, 2023
Abstract Background Clinical trials are an essential part of the medical research process, but trials are often canceled due to lack of enrollment. Clinical trial recruitment support systems can help increase the number of participants by finding more suitable subjects.
Romina Blasini, Kornelia Marta Buchowicz, Henning Schneider, Birgit Samans, Keywan Sohrabi   +4 more
openaire   +1 more source

OHDSI/PhenotypeLibrary: Release v3.16.0

, 2023
<p>See NEWS.md for release notes.</p ...
Gowtham Rao
core   +1 more source

Toward cross‐platform electronic health record‐driven phenotyping using Clinical Quality Language

Learning Health Systems, 2020
Introduction Electronic health record (EHR)‐driven phenotyping is a critical first step in generating biomedical knowledge from EHR data. Despite recent progress, current phenotyping approaches are manual, time‐consuming, error‐prone, and platform ...
Pascal S. Brandt, Richard C. Kiefer, Jennifer A. Pacheco, Prakash Adekkanattu, Evan T. Sholle, Faraz S. Ahmad, Jie Xu, Zhenxing Xu, Jessica S. Ancker, Fei Wang, Yuan Luo, Guoqian Jiang, Jyotishman Pathak, Luke V. Rasmussen   +13 more
doaj   +1 more source

Using the OHDSI network to develop and externally validate a patient-level prediction model for Heart Failure in Type II Diabetes Mellitus.

medRxiv, 2021
Introduction Heart Failure (HF) and Type 2 Diabetes Mellitus (T2DM) frequently coexist and exacerbate symptoms of each other. Treatments are available for T2DM that also provide beneficial treatment effects for HF. Guidelines recommend that patients with
Ross D. Williams, J. Reps, J. Kors, P. Ryan, E. Steyerberg, K. Verhamme, P. Rijnbeek   +6 more
semanticscholar   +1 more source