Finding a short and accurate decision rule in disjunctive normal form by exhaustive search. - Peter R. Rijnbeek; Jan A. Kors (Mach. Learn., 2010)

Alignment of 4D Coronary CTA with Monoplane X-ray Angiography. - Coert Metz; Michiel Schaap; Stefan Klein 001; Peter R. Rijnbeek; Lisan Neefjes; Nico Mollet; Carl J. Schultz; Patrick W. Serruys; Wiro J. Niessen; Theo van Walsum (AE-CAI, 2011)

Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. - George Hripcsak; Jon D. Duke; Nigam H. Shah; Christian G. Reich; Vojtech Huser; Martijn J. Schuemie; Marc A. Suchard; Rae Woong Park; Ian Chi Kei Wong; Peter R. Rijnbeek; Johan van der Lei; Nicole Pratt; et al. (MedInfo, 2015)

Accuracy of an automated knowledge base for identifying drug adverse reactions. - Erica A. Voss; Richard D. Boyce; Patrick B. Ryan; Johan van der Lei; Peter R. Rijnbeek; Martijn J. Schuemie (J. Biomed. Informatics, 2017)

A Methodology to Perform Semi-automatic Distributed EHR Database Queries. - Olga Fajarda; Luís A. Bastião Silva; Peter R. Rijnbeek; Michel Van Speybroeck; José Luís Oliveira (HEALTHINF, 2018)

Exploring the Value of Electronic Health Records from Multiple Datasets. - Olga Fajarda; Alina Trifan; Michel Van Speybroeck; Peter R. Rijnbeek; José Luís Oliveira (BIOSTEC (Selected Papers), 2018)

Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. - Jenna Marie Reps; Martijn J. Schuemie; Marc A. Suchard; Patrick B. Ryan; Peter R. Rijnbeek (J. Am. Medical Informatics Assoc., 2018)

Supplementing claims data analysis using self-reported data to develop a probabilistic phenotype model for current smoking status. - Jenna Marie Reps; Peter R. Rijnbeek; Patrick B. Ryan (J. Biomed. Informatics, 2019)

TASKA: A modular task management system to support health research studies. - João Rafael Almeida; Rosa Gini; Giuseppe Roberto; Peter R. Rijnbeek; José Luís Oliveira (BMC Medical Informatics Decis. Mak., 2019)

How little data do we need for patient-level prediction? - Luis H. John; Jan A. Kors; Jenna Marie Reps; Patrick B. Ryan; Peter R. Rijnbeek (CoRR, 2020)

A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data. - 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; et al. (Comput. Methods Programs Biomed., 2021)

Increasing trust in real-world evidence through evaluation of observational data quality. - Clair Blacketer; Frank J. DeFalco; Patrick B. Ryan; Peter R. Rijnbeek (J. Am. Medical Informatics Assoc., 2021)

Design matters in patient-level prediction: evaluation of a cohort vs. case-control design when developing predictive models in observational healthcare datasets. - Jenna Marie Reps; Patrick B. Ryan; Peter R. Rijnbeek; Martijn J. Schuemie (J. Big Data, 2021)

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies. - Aniek F. Markus; Jan A. Kors; Peter R. Rijnbeek (J. Biomed. Informatics, 2021)

An empirical analysis of dealing with patients who are lost to follow-up when developing prognostic models using a cohort design. - Jenna Marie Reps; Peter R. Rijnbeek; Alana Cuthbert; Patrick B. Ryan; Nicole Pratt; Martijn J. Schuemie (BMC Medical Informatics Decis. Mak., 2021)

Why predicting risk can't identify 'risk factors': empirical assessment of model stability in machine learning across observational health databases. - Aniek F. Markus; Peter R. Rijnbeek; Jenna Marie Reps (MLHC, 2022)

TreatmentPatterns: An R package to facilitate the standardized development and analysis of treatment patterns across disease domains. - Aniek F. Markus; Katia M. C. Verhamme; Jan A. Kors; Peter R. Rijnbeek (Comput. Methods Programs Biomed., 2022)

Logistic regression models for patient-level prediction based on massive observational data: Do we need all data? - Luis H. John; Jan A. Kors; Jenna Marie Reps; Patrick B. Ryan; Peter R. Rijnbeek (Int. J. Medical Informatics, 2022)

Use of unstructured text in prognostic clinical prediction models: a systematic review. - Tom M. Seinen; Egill A. Fridgeirsson; Solomon Ioannou; Daniel Jeannetot; Luis H. John; Jan A. Kors; Aniek F. Markus; Victor Pera; Alexandros Rekkas; Ross D. Williams; Cynthia Yang; Erik M. van Mulligen; et al. (J. Am. Medical Informatics Assoc., 2022)

Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review. - Cynthia Yang; Jan A. Kors; Solomon Ioannou; Luis H. John; Aniek F. Markus; Alexandros Rekkas; Maria A. J. de Ridder; Tom M. Seinen; Ross D. Williams; Peter R. Rijnbeek (J. Am. Medical Informatics Assoc., 2022)

Learning patient-level prediction models across multiple healthcare databases: evaluation of ensembles for increasing model transportability. - Jenna Marie Reps; Ross D. Williams; Martijn J. Schuemie; Patrick B. Ryan; Peter R. Rijnbeek (BMC Medical Informatics Decis. Mak., 2022)

A High-Fidelity Combined ATC-Rxnorm Drug Hierarchy for Large-Scale Observational Research. - Anna Ostropolets; Polina Talapova; Marcel de Wilde; Hamed Abedtash; Peter R. Rijnbeek; Christian G. Reich (MedInfo, 2023)

Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research. - Martijn J. Schuemie; Jenna Reps; Adam Black; Frank J. DeFalco; Lee Evans; Egill A. Fridgeirsson; James P. Gilbert; Chris Knoll; Martin Lavallee; Gowtham A. Rao; Peter R. Rijnbeek; Katy Sadowski; et al. (MedInfo, 2023)

Challenges of Estimating Global Feature Importance in Real-World Health Care Data. - Aniek F. Markus; Egill A. Fridgeirsson; Jan A. Kors; Katia M. C. Verhamme; Peter R. Rijnbeek (MIE, 2023)

The DELPHI Library: Improving Model Validation, Transparency and Dissemination Through a Centralised Library of Prediction Models. - Ross D. Williams; Sicco den Otter; Jenna Marie Reps; Peter R. Rijnbeek (MIE, 2023)

Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability? - Cynthia Yang; Egill A. Fridgeirsson; Jan A. Kors; Jenna Marie Reps; Peter R. Rijnbeek; Jenna Wong; Ross D. Williams (MIE, 2023)

A standardized framework for risk-based assessment of treatment effect heterogeneity in observational healthcare databases. - Alexandros Rekkas; David van Klaveren; Patrick B. Ryan; Ewout W. Steyerberg; David M. Kent; Peter R. Rijnbeek (npj Digit. Medicine, 2023)

The added value of text from Dutch general practitioner notes in predictive modeling. - Tom M. Seinen; Jan A. Kors; Erik M. van Mulligen; Egill A. Fridgeirsson; Peter R. Rijnbeek (J. Am. Medical Informatics Assoc., 2023)

European Health Data & Evidence Network - learnings from building out a standardized international health data network. - Erica A. Voss; Clair Blacketer; Sebastiaan van Sandijk; Maxim Moinat; Michael Kallfelz; Michel Van Speybroeck; Daniel Prieto-Alhambra; Martijn J. Schuemie; Peter R. Rijnbeek (J. Am. Medical Informatics Assoc., 2023)

Assessing the feasibility of observational data sources for multicenter clinical studies. - João Rafael Almeida; Peter R. Rijnbeek; Maxim Moinat; José Luís Oliveira (CBMS, 2024)

Comparison of deep learning and conventional methods for disease onset prediction. - 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 (CoRR, 2024)

Using clinical text to refine unspecific condition codes in Dutch general practitioner EHR data. - Tom M. Seinen; Jan A. Kors; Erik M. van Mulligen; Egill A. Fridgeirsson; Katia M. C. Verhamme; Peter R. Rijnbeek (Int. J. Medical Informatics, 2024)

Comparing penalization methods for linear models on large observational health data. - Egill A. Fridgeirsson; Ross D. Williams; Peter R. Rijnbeek; Marc A. Suchard; Jenna Marie Reps (J. Am. Medical Informatics Assoc., 2024)

Annotation-preserving machine translation of English corpora to validate Dutch clinical concept extraction tools. - Tom M. Seinen; Jan A. Kors; Erik M. van Mulligen; Peter R. Rijnbeek (J. Am. Medical Informatics Assoc., 2024)

OHDSI Standardized Vocabularies - a large-scale centralized reference ontology for international data harmonization. - Christian G. Reich; Anna Ostropolets; Patrick B. Ryan; Peter R. Rijnbeek; Martijn J. Schuemie; Alexander Davydov; Dmitry Dymshyts; George Hripcsak (J. Am. Medical Informatics Assoc., 2024)

Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data. - Cynthia Yang; Egill A. Fridgeirsson; Jan A. Kors; Jenna Marie Reps; Peter R. Rijnbeek (J. Big Data, 2024)