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ORCIDPeter R. Rijnbeek
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2020 – today
- 2024
[j23]Tom M. Seinen
, Jan A. Kors, Erik M. van Mulligen, Egill A. Fridgeirsson, Katia M. C. Verhamme, Peter R. Rijnbeek:
Using clinical text to refine unspecific condition codes in Dutch general practitioner EHR data. Int. J. Medical Informatics 189: 105506 (2024)- [j22]Christian G. Reich, Anna Ostropolets, Patrick B. Ryan, Peter R. Rijnbeek, Martijn J. Schuemie, Alexander Davydov, Dmitry Dymshyts, George Hripcsak:
OHDSI Standardized Vocabularies - a large-scale centralized reference ontology for international data harmonization. J. Am. Medical Informatics Assoc. 31(3): 583-590 (2024) - [j21]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): 1514-1521 (2024) - [j20]Tom M. Seinen, Jan A. Kors, Erik M. van Mulligen, Peter R. Rijnbeek:
Annotation-preserving machine translation of English corpora to validate Dutch clinical concept extraction tools. J. Am. Medical Informatics Assoc. 31(8): 1725-1734 (2024) - [j19]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): 7 (2024) - [c11]João Rafael Almeida, Peter R. Rijnbeek, Maxim Moinat, José Luís Oliveira:
Assessing the feasibility of observational data sources for multicenter clinical studies. CBMS 2024: 406-411 - 2023
- [j18]Tom M. Seinen, Jan A. Kors, Erik M. van Mulligen, Egill A. Fridgeirsson, Peter R. Rijnbeek:
The added value of text from Dutch general practitioner notes in predictive modeling. J. Am. Medical Informatics Assoc. 30(12): 1973-1984 (2023) - [j17]Erica A. Voss, Clair Blacketer, Sebastiaan van Sandijk, Maxim Moinat, Michael Kallfelz, Michel Van Speybroeck, Daniel Prieto-Alhambra, Martijn J. Schuemie, Peter R. Rijnbeek:
European Health Data & Evidence Network - learnings from building out a standardized international health data network. J. Am. Medical Informatics Assoc. 31(1): 209-219 (2023) - [j16]Alexandros Rekkas, David van Klaveren, Patrick B. Ryan, Ewout W. Steyerberg, David M. Kent, Peter R. Rijnbeek:
A standardized framework for risk-based assessment of treatment effect heterogeneity in observational healthcare databases. npj Digit. Medicine 6 (2023) - [c10]Anna Ostropolets, Polina Talapova, Marcel de Wilde, Hamed Abedtash, Peter R. Rijnbeek, Christian G. Reich:
A High-Fidelity Combined ATC-Rxnorm Drug Hierarchy for Large-Scale Observational Research. MedInfo 2023: 53-57 - [c9]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, Anthony G. Sena, Joel N. Swerdel, Ross D. Williams, Marc A. Suchard:
Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research. MedInfo 2023: 966-970 - [c8]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: 129-130 - [c7]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: 139-140 - [c6]Aniek F. Markus, Egill A. Fridgeirsson, Jan A. Kors, Katia M. C. Verhamme, Peter R. Rijnbeek:
Challenges of Estimating Global Feature Importance in Real-World Health Care Data. MIE 2023: 1057-1061 - 2022
- [j15]Aniek F. Markus, Katia M. C. Verhamme, Jan A. Kors, Peter R. Rijnbeek:
TreatmentPatterns: An R package to facilitate the standardized development and analysis of treatment patterns across disease domains. Comput. Methods Programs Biomed. 225: 107081 (2022) - [j14]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: 104762 (2022) - [j13]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:
Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review. J. Am. Medical Informatics Assoc. 29(5): 983-989 (2022) - [j12]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, Peter R. Rijnbeek:
Use of unstructured text in prognostic clinical prediction models: a systematic review. J. Am. Medical Informatics Assoc. 29(7): 1292-1302 (2022) - [j11]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): 142 (2022) - [c5]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: 828-852 - 2021
- [j10]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: 106394 (2021) - [j9]Clair Blacketer, Frank J. DeFalco, Patrick B. Ryan, Peter R. Rijnbeek:
Increasing trust in real-world evidence through evaluation of observational data quality. J. Am. Medical Informatics Assoc. 28(10): 2251-2257 (2021) - [j8]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): 108 (2021) - [j7]Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek:
The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies. J. Biomed. Informatics 113: 103655 (2021) - [j6]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): 43 (2021) - 2020
- [i2]Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek:
The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and evaluation strategies. CoRR abs/2007.15911 (2020) - [i1]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 abs/2008.07361 (2020)
2010 – 2019
- 2019
- [j5]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) - [j4]João Rafael Almeida, Rosa Gini, Giuseppe Roberto, Peter R. Rijnbeek, José Luís Oliveira:
TASKA: A modular task management system to support health research studies. BMC Medical Informatics Decis. Mak. 19(1): 121:1-121:9 (2019) - 2018
- [j3]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): 969-975 (2018) - [c4]Olga Fajarda, Luís A. Bastião Silva, Peter R. Rijnbeek, Michel Van Speybroeck, José Luís Oliveira:
A Methodology to Perform Semi-automatic Distributed EHR Database Queries. HEALTHINF 2018: 127-134 - [c3]Olga Fajarda, Alina Trifan, Michel Van Speybroeck, Peter R. Rijnbeek, José Luís Oliveira:
Exploring the Value of Electronic Health Records from Multiple Datasets. BIOSTEC (Selected Papers) 2018: 367-383 - 2017
- [j2]Erica A. Voss, Richard D. Boyce, Patrick B. Ryan, Johan van der Lei, Peter R. Rijnbeek, Martijn J. Schuemie:
Accuracy of an automated knowledge base for identifying drug adverse reactions. J. Biomed. Informatics 66: 72-81 (2017) - 2015
- [c2]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, G. Niklas Norén, Yu-Chuan Li, Paul E. Stang, David Madigan, Patrick B. Ryan:
Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. MedInfo 2015: 574-578 - 2011
- [c1]Coert Metz, Michiel Schaap, Stefan Klein, Peter R. Rijnbeek, Lisan Neefjes, Nico Mollet, Carl J. Schultz, Patrick W. Serruys, Wiro J. Niessen, Theo van Walsum:
Alignment of 4D Coronary CTA with Monoplane X-ray Angiography. AE-CAI 2011: 106-116 - 2010
- [j1]Peter R. Rijnbeek, Jan A. Kors:
Finding a short and accurate decision rule in disjunctive normal form by exhaustive search. Mach. Learn. 80(1): 33-62 (2010)
Coauthor Index
aka: Jenna Marie Reps
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