This paper is in the following e-collection/theme issue:

Data Science (307) Clinical Informatics (1169) Natural Language Processing (804) Electronic Health Records (1188) Clinical Information and Decision Making (1665) mHealth for Data Collection and Research (1087) Big Data (282) Machine Learning (1748) Information Retrieval (325) Health Information Exchange (125)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66910, first published .
Using Structured Codes and Free-Text Notes to Measure Information Complementarity in Electronic Health Records: Feasibility and Validation Study

Using Structured Codes and Free-Text Notes to Measure Information Complementarity in Electronic Health Records: Feasibility and Validation Study

Using Structured Codes and Free-Text Notes to Measure Information Complementarity in Electronic Health Records: Feasibility and Validation Study

Authors of this article:

Tom M Seinen1 Author Orcid Image ;   Jan A Kors1 Author Orcid Image ;   Erik M van Mulligen1 Author Orcid Image ;   Peter R Rijnbeek1 Author Orcid Image
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Tom M Seinen   1 , MSc ;   Jan A Kors   1 , PhD ;   Erik M van Mulligen   1 , PhD ;   Peter R Rijnbeek   1 , PhD

1 Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands

Corresponding Author:

  • Tom M Seinen, MSc
  • Department of Medical Informatics
  • Erasmus University Medical Center
  • Dr. Molewaterplein 40
  • Rotterdam, 3015 GD
  • The Netherlands
  • Phone: 31 010 7044122
  • Email: t.seinen@erasmusmc.nl