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

Machine Learning (2134) Precision Medicine and Genetics (83) AI applications in genomics and pathology informatics, including ‘Generative AI’ (22) Cardiac Risk and Cardiac Risk Calculators (110) Tools, Programs and Algorithms (388) Artificial Intelligence (2202)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/75565, first published .
Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study

Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study

Development of Venous Thromboembolism Risk Prediction Models Based on Whole Blood Gene Expression Profiling Using 20 Machine Learning Algorithms: Comprehensive Analysis Study

Authors of this article:

Yedong Huang1 Author Orcid Image ;   Xiaoyun Chen2 Author Orcid Image ;   Guannan Bai3 Author Orcid Image ;   Yajun Zhao4 Author Orcid Image ;   Dapeng Kuang5 Author Orcid Image ;   Lin Zhang6, 7 Author Orcid Image ;   Wei Lu8 Author Orcid Image
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