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

Machine Learning (1979) Data Science (347) Ontologies, Classifications, and Coding (309) Big Data (305) mHealth for Data Collection and Research (1166) Digital Health Reporting Standards, Quality and Transparency in e-Research (122) Electronic Health Records (1273) Development and Evaluation of Research Methods, Instruments and Tools (699)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54133, first published .
Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study

Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study

Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study

Authors of this article:

Doris Yang1 Author Orcid Image ;   Doudou Zhou2 Author Orcid Image ;   Steven Cai3 Author Orcid Image ;   Ziming Gan4 Author Orcid Image ;   Michael Pencina5 Author Orcid Image ;   Paul Avillach1 Author Orcid Image ;   Tianxi Cai1 Author Orcid Image ;   Chuan Hong5 Author Orcid Image
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Journals

  1. Mallya P, Henao R, Hong C, Wojdyla D, Schibler T, Manchanda V, Pencina M, Hall J, Zhao J. Automated Data Harmonization in Clinical Research: Natural Language Processing Approach. JMIR Formative Research 2025;9:e75608 View