Reps, Jenna

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

Weng, S. F., Reps, J., Kai, J., Garibaldi, J. M., & Qureshi, N. (2017) · PLOS ONE

Artificial Intelligence in HealthcareMachine Learning in Healthcare

Cited by 1,346

Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis: a multinational, retrospective study

Lane, J. C. E., Weaver, J., Kostka, K., Duarte-Salles, T., Abrahao, M. T. F., Alghoul, H., Alser, O., Alshammari, T. M., Biedermann, P., Banda, J. M., et al. (2020) · The Lancet Rheumatology

Rheumatoid Arthritis Research and TherapiesPharmacovigilance and Adverse Drug Reactions

Cited by 258

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data

Reps, J. M., Schuemie, M. J., Suchard, M. A., Ryan, P. B., & Rijnbeek, P. R. (2018) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 205

Perinatal depressive symptoms often start in the prenatal rather than postpartum period: results from a longitudinal study

Wilcox, M., McGee, B. A., Ionescu, D. F., Leonte, M., LaCross, L., Reps, J., & Wildenhaus, K. (2021) · Archives of Women's Mental Health

Maternal Mental Health During Pregnancy and PostpartumMaternal and Neonatal Healthcare

Cited by 83

Finding factors that predict treatment-resistant depression: results of a cohort study

Cepeda, M. S., Reps, J., & Ryan, P. (2018) · Depression and Anxiety

Treatment of Major DepressionMental Health Treatment and Access

Cited by 80

Finding treatment-resistant depression in real-world data: How a data-driven approach compares with expert-based heuristics

Cepeda, M. S., Reps, J., Fife, D., Blacketer, C., Stang, P., & Ryan, P. (2018) · Depression and Anxiety

Treatment of Major DepressionMental Health Treatment and Access

Cited by 50

Feasibility and evaluation of a large-scale external validation approach for patient-level prediction in an international data network: Validation of models predicting stroke in female patients newly diagnosed with atrial fibrillation

Reps, J. M., Williams, R. D., You, S. C., Falconer, T., Minty, E., Callahan, A., Ryan, P. B., Park, R. W., Lim, H.-S., & Rijnbeek, P. (2020) · BMC Medical Research Methodology

Atrial Fibrillation Management and OutcomesMachine Learning in Healthcare

Cited by 40

Health-Analytics Data to Evidence Suite (HADES): open-source software for observational research.

Schuemie, M., Reps, J., Black, A., Defalco, F., Evans, L., Fridgeirsson, E., Gilbert, J. P., Knoll, C., Lavallee, M., Rao, G. A., et al. (2024) · Studies in Health Technology and Informatics

Machine Learning in HealthcareMedical Coding and Health Information

Cited by 28

Treatment resistant depression incidence estimates from studies of health insurance databases depend strongly on the details of the operating definition

Fife, D., Reps, J., Cepeda, M. S., Stang, P., Blacketer, M., & Singh, J. (2018) · Heliyon

Treatment of Major DepressionMental Health Treatment and Access

Cited by 22

Similar Risk of Kidney Failure among Patients with Blinding Diseases Who Receive Ranibizumab, Aflibercept, and Bevacizumab

Cai, C. X., Nishimura, A., Bowring, M. G., Westlund, E., Tran, D., Ng, J. H., Nagy, P., Cook, M., McLeggon, J.-A., DuVall, S. L., et al. (2024) · Ophthalmology Retina

Retinal Diseases and TreatmentsDrug-Induced Ocular Toxicity

Cited by 20