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Showing results (281-290 of 359) with videos related to

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Biorxiv : the Preprint Server for Biology|June 3, 2024
Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran ProgramAlex Rodriguez, Youngdae Kim, Tarak Nath Nandi, et al.
The Lancet. Rheumatology|March 6, 2023
Autoantibodies against citrullinated and native proteins and prediction of rheumatoid arthritis-associated interstitial lung disease: A nested case-control studyVanessa L Kronzer, Keigo Hayashi, Kazuki Yoshida, et al.
Journal of the American Heart Association|April 30, 2024
Interplay Between Systemic Inflammation, Myocardial Injury, and Coronary Microvascular Dysfunction in Rheumatoid Arthritis: Results From the LiiRA StudyBrittany Weber, Dana Weisenfeld, Elena Massarotti, et al.
Journal of the American Medical Informatics Association : JAMIA|March 1, 2012
Portability of an algorithm to identify rheumatoid arthritis in electronic health recordsRobert J Carroll, Will K Thompson, Anne E Eyler, et al.
Journal of the American Medical Informatics Association : JAMIA|March 14, 2024
Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data usersJacqueline Honerlaw, Yuk-Lam Ho, Francesca Fontin, et al.
Plos One|November 19, 2013
Modeling disease severity in multiple sclerosis using electronic health recordsZongqi Xia, Elizabeth Secor, Lori B Chibnik, et al.
American Journal of Epidemiology|October 7, 2025
Improving classification of myocardial infarction with machine learning in a diverse populationAlicia Chen, Chuan Hong, Yuk Lam Ho, et al.
Plos One|May 13, 2021
Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran ProgramRebecca J Song, Yuk-Lam Ho, Petra Schubert, et al.
American Journal of Human Genetics|December 25, 2012
Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritisDorothée Diogo, Fina Kurreeman, Eli A Stahl, et al.
Nature Protocols|November 22, 2019
High-throughput phenotyping with electronic medical record data using a common semi-supervised approach (PheCAP)Yichi Zhang, Tianrun Cai, Sheng Yu, et al.
Pageof 36

Showing results (281-290 of 359) with videos related to

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Pageof 36
Biorxiv : the Preprint Server for Biology|June 3, 2024
Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran ProgramAlex Rodriguez, Youngdae Kim, Tarak Nath Nandi, et al.
The Lancet. Rheumatology|March 6, 2023
Autoantibodies against citrullinated and native proteins and prediction of rheumatoid arthritis-associated interstitial lung disease: A nested case-control studyVanessa L Kronzer, Keigo Hayashi, Kazuki Yoshida, et al.
Journal of the American Heart Association|April 30, 2024
Interplay Between Systemic Inflammation, Myocardial Injury, and Coronary Microvascular Dysfunction in Rheumatoid Arthritis: Results From the LiiRA StudyBrittany Weber, Dana Weisenfeld, Elena Massarotti, et al.
Journal of the American Medical Informatics Association : JAMIA|March 1, 2012
Portability of an algorithm to identify rheumatoid arthritis in electronic health recordsRobert J Carroll, Will K Thompson, Anne E Eyler, et al.
Journal of the American Medical Informatics Association : JAMIA|March 14, 2024
Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data usersJacqueline Honerlaw, Yuk-Lam Ho, Francesca Fontin, et al.
Plos One|November 19, 2013
Modeling disease severity in multiple sclerosis using electronic health recordsZongqi Xia, Elizabeth Secor, Lori B Chibnik, et al.
American Journal of Epidemiology|October 7, 2025
Improving classification of myocardial infarction with machine learning in a diverse populationAlicia Chen, Chuan Hong, Yuk Lam Ho, et al.
Plos One|May 13, 2021
Phenome-wide association of 1809 phenotypes and COVID-19 disease progression in the Veterans Health Administration Million Veteran ProgramRebecca J Song, Yuk-Lam Ho, Petra Schubert, et al.
American Journal of Human Genetics|December 25, 2012
Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritisDorothée Diogo, Fina Kurreeman, Eli A Stahl, et al.
Nature Protocols|November 22, 2019
High-throughput phenotyping with electronic medical record data using a common semi-supervised approach (PheCAP)Yichi Zhang, Tianrun Cai, Sheng Yu, et al.
Pageof 36