John H. Holmes

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Professor of Medical Informatics in Epidemiology in Biostatistics and Epidemiology at the Hospital of the University of Pennsylvania
Senior Fellow, Leonard Davis Institute of Health Economics, Wharton School, University of Pennsylvania
Senior Scholar, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine
Senior Fellow, Center for Public Health Initiatives, School of Medicine University of Pennsylvania
Associate Director for Medical Informatics, Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine
Department: Biostatistics and Epidemiology

Contact information
401 Blockley Hall
423 Guardian Drive
Philadelphia, PA 19104
Office: 215-898-4833
Fax: 215-573-5325
Education:
A.B. (Sociology)
University of Pennsylvania, 1976.
M.S. (Information Systems)
Drexel University, 1987.
Ph.D. (Information Science)
Drexel University, 1996.
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Description of Research Expertise

medical informatics; data mining; evolutionary computation; machine learning; artificial intelligence; database design and implementation for clinical research; medical decision making;

Description of Itmat Expertise

Dr. Holmes is studying epidemiologic informatics, using large databases for clinical research, and the development of evolutionary computational approaches for knowledge discovery (data mining). Research includes creating and applying knowledge discovery methods for the analysis of gene-environment interactions and pursuit of associations between HLA residue mismatch patterns in renal allografts and various clinical outcomes.

Selected Publications

Golovco S, Montovani M, Combi C, Holmes JH: Acute kidney prediction with gradient boosting decision trees enriched with temporal features. The 2nd Workshop on Machine Learning in Healthcare Data for Precision Medicine at the 10th IEEE International Conference on Healthcare Informatics, Rochester, MN March 2022 Notes: Peer-reviewed, full-length, indexed conference paper , accepted March 7, 2022.

Glanz K, Avelis J, Kwoing PL, Holmes JH: Correlates of Attitudes Toward COVID-19 Policies and Prevention Practices in Six States. Journal of Public Health Research 11(2), 2022 Notes: Accepted April 30, 2022. In press.

Klann JG…Holmes JH, Xia Z, Brat GA, Murphy SN: Distinguishing admissions specifically for COVID-19 from incidental SARS-CoV-2 admissions: A national EHR research consortium study. medRxiv Page: Online ahead of print, Feb 2022 Notes: doi: 10.1101/2022.02.10.22270728.

Weber GM,…,Holmes JH, et al.: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: a 4CE Consortium Study. Journal of Medical Internet Research 23(10): e31400, Oct 2021.

Van Pelt AE, Beidas RS, Scott JC, Moore TM, Ahmed CV, Morales KH, Thuto B, Tshume O, Gur RC, Holmes JH, Matshaba M, Lowenthal ED. : Acceptability of a computerized neurocognitive battery to identify cognitive impairments among children and adolescents in Botswana. Global Implementation Research and Applications 1: 267-278, Nov 2021.

Saine ME, Szymczak JE, Moore TM, Bamford LP, Bard FK, Forde KA, Schnittker J, Holmes JH, Mitra N, Lo Re V: The impact of disease-related knowledge on perceptions of stigma among patients with hepatitis C virus (HCV) infection. PLoS One 16(10): e0258143, Oct 2021.

Holmes JH...Moore JH: Why is the electronic health record so challenging for research and clinical care? Methods of Information in Medicine 60(1-02): 32-48, May 2021.

Urbanowicz RJ, Holmes JH, Appleby D, Narasimhan V, Durburow S, Al-Naamani N, Fernando M, Kawut SM: A semi-automated term harmonization pipeline applied to pulmonary arterial hypertension clinical trials. Methods of Information in Medicine Page: Online ahead of print, Nov 2021.

Klann JG, …, Holmes JH, et al. : Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data. Journal of the American Medical Informatics Association 28(7): 1411-1420, Jul 2021.

Dagliati A, Geifman N, Peek N, Holmes JH, Sacchi L, Bellazzi R, Sajjadi SE, Tucker A.: Using topological data analysis and pseudo time series to infer temporal phenotypes from electronic health records. Artificial Intelligence in Medicine 108: 101930, Aug 2020.

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Last updated: 02/28/2024
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