Peter Rijnbeek

BioRelated/Noteworthy Publications
Peter Rijnbeek

Peter Rijnbeek, PhD
Associate Professor Health Data Science
Erasmus University Medical Center

Peter Rijnbeek, PhD, obtained his MSc (1996) in Electrical Engineering at the Technical University Delft. His PhD thesis, received from the Erasmus University Rotterdam, was on the development of a computer program to automatically interpret pediatric electrocardiograms. He is Assistant Professor at the Erasmus University Medical Center in Rotterdam where he is leading the health data science group at the Department of Medical Informatics (www.healthdatascience.nl).

His research interests include computerized analysis of the electrocardiogram, pattern recognition, machine learning and predictive modeling using clinical data. He had a leading role in several large European projects related to secondary use of health care database. He is co-leading the European Health Data and Evidence Network project funded by the European Commission that aims to standardize a large amount of databases to the OMOP-CDM in the upcoming 5 years and create a high quality European data network. Peter is the coordinator of the European OHDSI chapter that organizes a yearly symposium (www.ohdsi-europe.org) that supports the adoption of the OMOP-CDM.

In OHDSI he is co-leading the Patient-Level Prediction working group together with Jenna Reps that built a framework on top of the OMOP-CDM for large-scale development and validation of prediction models across the world (www.github.com/ohdsi/PatientLevelPrediction).

Reps JM, Schuemie MJ, Suchard MA, Ryan PB, Rijnbeek PR. Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. J Am Med Inform Assoc. 2018 Aug 1;25(8):969-975

Voss EA, Boyce RD, Ryan PB, van der Lei J, Rijnbeek PR, Schuemie MJ. Accuracy of an automated knowledge base for identifying drug adverse reactions. Journal of Biomedical Informatics. 2017;66:72-81. Rijnbeek PR. Converting to a Common Data Model: What is Lost in Translation? (vol 37, pg 893, 2014). Drug Safety. 2014;37(12):1073-.

Hripcsak G, Duke JD, Shah NH, Reich CG, Huser V, Schuemie MJ, Suchard MA, Park RW, Wong IC, Rijnbeek PR, van der Lei J, Pratt N, Norén GN, Li YC, Stang PE, Madigan D, Ryan PB Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. Stud Health Technol Inform. 2015;(216):574–8.

Rijnbeek PR, Kors JA, Finding a short and accurate decision rule in disjunctive normal form by exhaustive search. Machine
Learning, 2010, 80(1): p. 33-62.

Trifirò G., P. M. Coloma, P. R. Rijnbeek, S. Romio, B. Mosseveld, D. Weibel, J. Bonhoeffer, M. Schuemie, J. van der Lei and M. Sturkenboom, 2014 Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: why and how? Journal of Internal Medicine. Volume 275, Issue 6, pages 551–561

 

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