Jenna Marie Reps

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 19

Top Venues

CoRR

J. Am. Medical Informatics Assoc.

ICDM Workshops

J. Big Data

University of Nottingham, UK (PHD)

Education History

University of Nottingham, UK

PHD

Publications

Cynthia Yang, Egill A. Fridgeirsson, Jan A. Kors, Jenna Marie Reps, Peter R. Rijnbeek
Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data. J. Big Data 11 (1) (2024)
Egill A. Fridgeirsson, Ross D. Williams, Peter R. Rijnbeek, Marc A. Suchard, Jenna Marie Reps
Comparing penalization methods for linear models on large observational health data. J. Am. Medical Informatics Assoc. 31 (7) (2024)
Ross D. Williams, Sicco den Otter, Jenna Marie Reps, Peter R. Rijnbeek
The DELPHI Library: Improving Model Validation, Transparency and Dissemination Through a Centralised Library of Prediction Models. MIE (2023)
Cynthia Yang, Egill A. Fridgeirsson, Jan A. Kors, Jenna Marie Reps, Peter R. Rijnbeek, Jenna Wong, Ross D. Williams
Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability? MIE (2023)
Aniek F. Markus, Peter R. Rijnbeek, Jenna Marie Reps
Why predicting risk can't identify 'risk factors': empirical assessment of model stability in machine learning across observational health databases. MLHC (2022)
Jenna Marie Reps, Ross D. Williams, Martijn J. Schuemie, Patrick B. Ryan, Peter R. Rijnbeek
Learning patient-level prediction models across multiple healthcare databases: evaluation of ensembles for increasing model transportability. BMC Medical Informatics Decis. Mak. 22 (1) (2022)
Luis H. John, Jan A. Kors, Jenna Marie Reps, Patrick B. Ryan, Peter R. Rijnbeek
Logistic regression models for patient-level prediction based on massive observational data: Do we need all data? Int. J. Medical Informatics 163 (2022)
Jenna Marie Reps, Peter R. Rijnbeek, Alana Cuthbert, Patrick B. Ryan, Nicole Pratt, Martijn J. Schuemie
An empirical analysis of dealing with patients who are lost to follow-up when developing prognostic models using a cohort design. BMC Medical Informatics Decis. Mak. 21 (1) (2021)
Chungsoo Kim, Seng Chan You, Jenna Marie Reps, Jae Youn Cheong, Rae Woong Park
Machine-learning model to predict the cause of death using a stacking ensemble method for observational data. J. Am. Medical Informatics Assoc. 28 (6) (2021)
Jenna Marie Reps, Patrick B. Ryan, Peter R. Rijnbeek, Martijn J. Schuemie
Design matters in patient-level prediction: evaluation of a cohort vs. case-control design when developing predictive models in observational healthcare datasets. J. Big Data 8 (1) (2021)
Sara Khalid, Cynthia Yang, Clair Blacketer, Talita Duarte-Salles, Sergio Fernández-Bertolín, Chungsoo Kim, Rae Woong Park, Jimyung Park, Martijn J. Schuemie, Anthony G. Sena, Marc A. Suchard, Seng Chan You, Peter R. Rijnbeek, Jenna Marie Reps
A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data. Comput. Methods Programs Biomed. 211 (2021)
Luis H. John, Jan A. Kors, Jenna Marie Reps, Patrick B. Ryan, Peter R. Rijnbeek
How little data do we need for patient-level prediction? CoRR (2020)
Uwe Aickelin, Jenna Marie Reps, Peer-Olaf Siebers, Peng Li
Using simulation to incorporate dynamic criteria into multiple criteria decision-making. CoRR (2020)
Jenna Marie Reps, Peter R. Rijnbeek, Patrick B. Ryan
Supplementing claims data analysis using self-reported data to develop a probabilistic phenotype model for current smoking status. J. Biomed. Informatics 97 (2019)
Uwe Aickelin, Jenna Marie Reps, Peer-Olaf Siebers, Peng Li
Using simulation to incorporate dynamic criteria into multiple criteria decision-making. J. Oper. Res. Soc. 69 (7) (2018)
Jenna Marie Reps, Martijn J. Schuemie, Marc A. Suchard, Patrick B. Ryan, Peter R. Rijnbeek
Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. J. Am. Medical Informatics Assoc. 25 (8) (2018)
Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Jack E. Gibson, Richard B. Hubbard
Supervised Adverse Drug Reaction Signalling Framework Imitating Bradford Hill's Causality Considerations. CoRR (2016)
Jenna Marie Reps, Uwe Aickelin, Richard B. Hubbard
Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining. Comput. Biol. Medicine 69 (2016)
Jenna Marie Reps, Uwe Aickelin, Richard B. Hubbard
Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining. CoRR (2016)
Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Jack E. Gibson, Richard B. Hubbard
A supervised adverse drug reaction signalling framework imitating Bradford Hill's causality considerations. J. Biomed. Informatics 56 (2015)
Jenna Marie Reps, Uwe Aickelin
Incorporating Spontaneous Reporting System Data to Aid Causal Inference in Longitudinal Healthcare Data. ICDM Workshops (2014)
Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard
A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE J. Biomed. Health Informatics 18 (2) (2014)
Jenna Marie Reps, Uwe Aickelin, Jonathan M. Garibaldi
Tuning a multiple classifier system for side effect discovery using genetic algorithms. IEEE Congress on Evolutionary Computation (2014)
Jenna Marie Reps, Uwe Aickelin, Jiangang Ma, Yanchun Zhang
Refining Adverse Drug Reactions Using Association Rule Mining for Electronic Healthcare Data. ICDM Workshops (2014)
Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard
Comparison of algorithms that detect drug side effects using electronic healthcare databases. Soft Comput. 17 (12) (2013)

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Publication Activity (10 Years)

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Jenna Marie Reps