Jenna Reps

3.3k total citations · 1 hit paper
61 papers, 1.7k citations indexed

About

Jenna Reps is a scholar working on Artificial Intelligence, Epidemiology and Toxicology. According to data from OpenAlex, Jenna Reps has authored 61 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 11 papers in Epidemiology and 8 papers in Toxicology. Recurrent topics in Jenna Reps's work include Machine Learning in Healthcare (19 papers), Pharmacovigilance and Adverse Drug Reactions (8 papers) and Chronic Disease Management Strategies (7 papers). Jenna Reps is often cited by papers focused on Machine Learning in Healthcare (19 papers), Pharmacovigilance and Adverse Drug Reactions (8 papers) and Chronic Disease Management Strategies (7 papers). Jenna Reps collaborates with scholars based in United States, Netherlands and United Kingdom. Jenna Reps's co-authors include Jonathan M. Garibaldi, Stephen Weng, Nadeem Qureshi, Joe Kai, Patrick Ryan, Peter R. Rijnbeek, M. Soledad Cepeda, Martijn J. Schuemie, Marc A. Suchard and Uwe Aickelin and has published in prestigious journals such as PLoS ONE, Statistics in Medicine and Journal of the Operational Research Society.

In The Last Decade

Jenna Reps

59 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

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

2017 820 citations Stephen Weng, Jenna Reps et al. PLoS ONE profile →

Peers

Jenna Reps

HIM

CCM

EPIDE

Hsuan‐Chia Yang Taiwan

Patrick Tighe United States

Md. Mohaimenul Islam Taiwan

Tahmina Nasrin Poly Taiwan

Evangelia Christodoulou Germany

Lemuel R. Waitman United States

Michael A. Pfeffer United States

Stephen Weng United Kingdom

Taxiarchis Botsis United States

Sooyoung Yoo South Korea

Hsuan‐Chia Yang Taiwan

Jenna Reps

373 ×0.7

308 ×0.6

HIM

164 ×0.6

CCM

466 ×2.2

EPIDE

139 ×0.7

Citations per year, relative to Jenna Reps Jenna Reps (= 1×) peers Hsuan‐Chia Yang

Countries citing papers authored by Jenna Reps

Since Specialization

Citations

This map shows the geographic impact of Jenna Reps's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jenna Reps with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jenna Reps more than expected).

Fields of papers citing papers by Jenna Reps

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jenna Reps. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jenna Reps. The network helps show where Jenna Reps may publish in the future.

Co-authorship network of co-authors of Jenna Reps

This figure shows the co-authorship network connecting the top 25 collaborators of Jenna Reps. A scholar is included among the top collaborators of Jenna Reps based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jenna Reps. Jenna Reps is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

El‐Hay, Tal, Jenna Reps, & Chen Yanover. (2025). Extensive benchmarking of a method that estimates external model performance from limited statistical characteristics. npj Digital Medicine. 8(1). 59–59. 1 indexed citations

Reps, Jenna, Egill A. Friðgeirsson, Chungsoo Kim, et al.. (2025). Finding a constrained number of predictor phenotypes for multiple outcome prediction. BMJ Health & Care Informatics. 32(1). e101227–e101227.

Markus, Aniek F., Egill A. Friðgeirsson, Luis H. John, et al.. (2025). Implementation and Updating of Clinical Prediction Models: A Systematic Review. PubMed. 3(3). 100228–100228. 2 indexed citations

Tong, Jiayi, Jenna Reps, Vitaly Lorman, et al.. (2024). Advancing Interpretable Regression Analysis for Binary Data: A Novel Distributed Algorithm Approach. Statistics in Medicine. 43(29). 5573–5582. 1 indexed citations

Friðgeirsson, Egill A., Ross D. Williams, Peter Rijnbeek, Marc A. Suchard, & Jenna Reps. (2024). Comparing penalization methods for linear models on large observational health data. Journal of the American Medical Informatics Association. 31(7). 1514–1521. 2 indexed citations

Yang, Cynthia, Egill A. Friðgeirsson, Jan A. Kors, Jenna Reps, & Peter R. Rijnbeek. (2024). Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data. Journal Of Big Data. 11(1). 30 indexed citations

Lee, Dong Yun, Byungjin Choi, Chungsoo Kim, et al.. (2023). Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study. Journal of Medical Internet Research. 25. e46165–e46165. 8 indexed citations

Williams, Ross D., Jenna Reps, Jan A. Kors, et al.. (2022). Using Iterative Pairwise External Validation to Contextualize Prediction Model Performance: A Use Case Predicting 1-Year Heart Failure Risk in Patients with Diabetes Across Five Data Sources. Drug Safety. 45(5). 563–570. 4 indexed citations

Chandran, Urmila, Jenna Reps, Robert Yang, et al.. (2022). Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care. Cancer Epidemiology Biomarkers & Prevention. 32(3). 337–343. 22 indexed citations

10.

Reps, Jenna, Patrick Ryan, Peter R. Rijnbeek, & Martijn J. Schuemie. (2021). Design matters in patient-level prediction: evaluation of a cohort vs. case-control design when developing predictive models in observational healthcare datasets. Journal Of Big Data. 8(1). 15 indexed citations

11.

Khalid, Sara, Cynthia Yang, Clair Blacketer, et al.. (2021). A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data. Computer Methods and Programs in Biomedicine. 211. 106394–106394. 25 indexed citations

12.

Nestsiarovich, Anastasiya, Jenna Reps, Michael E. Matheny, et al.. (2021). Predictors of diagnostic transition from major depressive disorder to bipolar disorder: a retrospective observational network study. Translational Psychiatry. 11(1). 642–642. 22 indexed citations

13.

Reps, Jenna, Patrick Ryan, & Peter R. Rijnbeek. (2021). Investigating the impact of development and internal validation design when training prognostic models using a retrospective cohort in big US observational healthcare data. BMJ Open. 11(12). e050146–e050146. 11 indexed citations

14.

Cepeda, M. Soledad, Martijn J. Schuemie, David M. Kern, Jenna Reps, & Carla M. Canuso. (2020). Frequency of rehospitalization after hospitalization for suicidal ideation or suicidal behavior in patients with depression. Psychiatry Research. 285. 112810–112810. 14 indexed citations

15.

Reps, Jenna, Peter R. Rijnbeek, & Patrick Ryan. (2019). Supplementing claims data analysis using self-reported data to develop a probabilistic phenotype model for current smoking status. Journal of Biomedical Informatics. 97. 103264–103264. 7 indexed citations

16.

Cepeda, M. Soledad, Jenna Reps, David M. Kern, & Paul Stang. (2019). Medical Conditions Predictive of Self-Reported Poor Health: Retrospective Cohort Study. JMIR Public Health and Surveillance. 6(1). e13018–e13018. 4 indexed citations

17.

Reps, Jenna, Martijn J. Schuemie, Marc A. Suchard, Patrick Ryan, & Peter R. Rijnbeek. (2018). Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. Journal of the American Medical Informatics Association. 25(8). 969–975. 119 indexed citations

18.

Todd, Ian, Ola H. Negm, Jenna Reps, et al.. (2017). A signalome screening approach in the autoinflammatory disease TNF receptor associated periodic syndrome (TRAPS) highlights the anti-inflammatory properties of drugs for repurposing. Pharmacological Research. 125(Pt B). 188–200. 8 indexed citations

19.

Weng, Stephen, Jenna Reps, Joe Kai, Jonathan M. Garibaldi, & Nadeem Qureshi. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data?. PLoS ONE. 12(4). e0174944–e0174944. 820 indexed citations breakdown →

20.

Vedhara, Kavita, Karen Dawe, Jeremy N. V. Miles, et al.. (2016). Illness Beliefs Predict Mortality in Patients with Diabetic Foot Ulcers. PLoS ONE. 11(4). e0153315–e0153315. 23 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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