Jenna Marie Reps

33 papers B 1Journal 26Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A lossless one-shot distributed algorithm for addressing heterogeneity in multi-site generalized linear models. J. Am. Medical Informatics Assoc. Bingyu Zhang, Qiong Wu, Jenna Marie Reps, Lu Li, Jiayi Tong, Yiwen Lu, Dazheng Zhang, Juan Manuel Ramírez-Anguita, Jiang Bian, Milou T. Brand, Thomas Falconer, Miguel A. Mayer, Ross D. Williams, Yong Chen
2026	J	`jnl`	Transfer-learning on federated observational healthcare data for prediction models using Bayesian sparse logistic regression with informed priors. J. Am. Medical Informatics Assoc. Kelly Mohe Li, Jenna Marie Reps, Akihiko Nishimura, Martijn J. Schuemie, Marc A. Suchard
2025	J	`jnl`	COLA-GLM: collaborative one-shot and lossless algorithms of generalized linear models for decentralized observational healthcare data. npj Digit. Medicine Qiong Wu, Jenna Marie Reps, Lu Li, Bingyu Zhang, Yiwen Lu, Jiayi Tong, Dazheng Zhang, Thomas Lumley, Milou T. Brand, Mui Van Zandt, Thomas Falconer, Xing He, Yu Huang, Haoyang Li, Chao Yan, Guojun Tang, Andrew E. Williams, Fei Wang, Jiang Bian, Bradley A. Malin, George Hripcsak, Martijn J. Schuemie, Yun Lu, Steve Drew, Jiayu Zhou, David A. Asch, Yong Chen
2025	J	`jnl`	Clinical semantics for lung cancer prediction. CoRR Luis H. John, Jan A. Kors, Jenna Marie Reps, Peter R. Rijnbeek, Egill A. Fridgeirsson
2025	J	`jnl`	Extensive benchmarking of a method that estimates external model performance from limited statistical characteristics. npj Digit. Medicine Tal El-Hay, Jenna Marie Reps, Chen Yanover
2025	J	`jnl`	Unlocking efficiency in real-world collaborative studies: a multi-site international study with one-shot lossless GLMM algorithm. npj Digit. Medicine Jiayi Tong, Jenna Marie Reps, Chongliang Luo, Yiwen Lu, Lu Li, Juan Manuel Ramírez-Anguita, Milou T. Brand, Scott L. DuVall, Thomas Falconer, Alex Mayer Fuentes, Xing He, Michael E. Matheny, Miguel A. Mayer, Bhavnisha K. Patel, Katherine Simon, Marc A. Suchard, Guojun Tang, Benjamin Viernes, Ross D. Williams, Mui Van Zandt, Fei Wang, Jiang Bian, Jiayu Zhou, David A. Asch, Yong Chen
2024	J	`jnl`	Comparing penalization methods for linear models on large observational health data. J. Am. Medical Informatics Assoc. Egill A. Fridgeirsson, Ross D. Williams, Peter R. Rijnbeek, Marc A. Suchard, Jenna Marie Reps
2024	J	`jnl`	Comparison of deep learning and conventional methods for disease onset prediction. CoRR Luis H. John, Chungsoo Kim, Jan A. Kors, Junhyuk Chang, Hannah Morgan-Cooper, Priya Desai, Chao Pang, Peter R. Rijnbeek, Jenna Marie Reps, Egill A. Fridgeirsson
2024	J	`jnl`	Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data. J. Big Data Cynthia Yang, Egill A. Fridgeirsson, Jan A. Kors, Jenna Marie Reps, Peter R. Rijnbeek
2023	—	`conf`	Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability? MIE Cynthia Yang, Egill A. Fridgeirsson, Jan A. Kors, Jenna Marie Reps, Peter R. Rijnbeek, Jenna Wong, Ross D. Williams
2023	—	`conf`	The DELPHI Library: Improving Model Validation, Transparency and Dissemination Through a Centralised Library of Prediction Models. MIE Ross D. Williams, Sicco den Otter, Jenna Marie Reps, Peter R. Rijnbeek
2022	J	`jnl`	Learning patient-level prediction models across multiple healthcare databases: evaluation of ensembles for increasing model transportability. BMC Medical Informatics Decis. Mak. Jenna Marie Reps, Ross D. Williams, Martijn J. Schuemie, Patrick B. Ryan, Peter R. Rijnbeek
2022	J	`jnl`	Logistic regression models for patient-level prediction based on massive observational data: Do we need all data? Int. J. Medical Informatics Luis H. John, Jan A. Kors, Jenna Marie Reps, Patrick B. Ryan, Peter R. Rijnbeek
2022	—	`conf`	Why predicting risk can't identify 'risk factors': empirical assessment of model stability in machine learning across observational health databases. MLHC Aniek F. Markus, Peter R. Rijnbeek, Jenna Marie Reps
2021	J	`jnl`	A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data. Comput. Methods Programs Biomed. 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
2021	J	`jnl`	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. Jenna Marie Reps, Peter R. Rijnbeek, Alana Cuthbert, Patrick B. Ryan, Nicole Pratt, Martijn J. Schuemie
2021	J	`jnl`	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 Jenna Marie Reps, Patrick B. Ryan, Peter R. Rijnbeek, Martijn J. Schuemie
2021	J	`jnl`	Machine-learning model to predict the cause of death using a stacking ensemble method for observational data. J. Am. Medical Informatics Assoc. Chungsoo Kim, Seng Chan You, Jenna Marie Reps, Jae Youn Cheong, Rae Woong Park
2020	J	`jnl`	How little data do we need for patient-level prediction? CoRR Luis H. John, Jan A. Kors, Jenna Marie Reps, Patrick B. Ryan, Peter R. Rijnbeek
2020	J	`jnl`	Using simulation to incorporate dynamic criteria into multiple criteria decision-making. CoRR Uwe Aickelin, Jenna Marie Reps, Peer-Olaf Siebers, Peng Li
2019	J	`jnl`	Supplementing claims data analysis using self-reported data to develop a probabilistic phenotype model for current smoking status. J. Biomed. Informatics Jenna Marie Reps, Peter R. Rijnbeek, Patrick B. Ryan
2018	J	`jnl`	Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. J. Am. Medical Informatics Assoc. Jenna Marie Reps, Martijn J. Schuemie, Marc A. Suchard, Patrick B. Ryan, Peter R. Rijnbeek
2018	J	`jnl`	Using simulation to incorporate dynamic criteria into multiple criteria decision-making. J. Oper. Res. Soc. Uwe Aickelin, Jenna Marie Reps, Peer-Olaf Siebers, Peng Li
2016	J	`jnl`	Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining. Comput. Biol. Medicine Jenna Marie Reps, Uwe Aickelin, Richard B. Hubbard
2016	J	`jnl`	Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining. CoRR Jenna Marie Reps, Uwe Aickelin, Richard B. Hubbard
2016	J	`jnl`	Supervised Adverse Drug Reaction Signalling Framework Imitating Bradford Hill's Causality Considerations. CoRR Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Jack E. Gibson, Richard B. Hubbard
2015	J	`jnl`	A supervised adverse drug reaction signalling framework imitating Bradford Hill's causality considerations. J. Biomed. Informatics Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Jack E. Gibson, Richard B. Hubbard
2014	J	`jnl`	A Novel Semisupervised Algorithm for Rare Prescription Side Effect Discovery. IEEE J. Biomed. Health Informatics Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard
2014	—	`—`	Detecting adverse drug reactions in the general practice healthcare database. Jenna Marie Reps
2014	—	`conf`	Incorporating Spontaneous Reporting System Data to Aid Causal Inference in Longitudinal Healthcare Data. ICDM Workshops Jenna Marie Reps, Uwe Aickelin
2014	—	`conf`	Refining Adverse Drug Reactions Using Association Rule Mining for Electronic Healthcare Data. ICDM Workshops Jenna Marie Reps, Uwe Aickelin, Jiangang Ma, Yanchun Zhang
2014	B	`conf`	Tuning a multiple classifier system for side effect discovery using genetic algorithms. IEEE Congress on Evolutionary Computation Jenna Marie Reps, Uwe Aickelin, Jonathan M. Garibaldi
2013	J	`jnl`	Comparison of algorithms that detect drug side effects using electronic healthcare databases. Soft Comput. Jenna Marie Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard