Accessibility settings

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

Clinical Information and Decision Making (3540) Digital Health Reviews (3519) Tools, Programs and Algorithms (567) Genomics and Bioinformatics for Clinical Use (114) Machine Learning (3053) Stroke (311) Cardiac Risk and Cardiac Risk Calculators (165) Artificial Intelligence (4543) AI applications in genomics and pathology informatics, including generative AI (43)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/85654, first published .
Multiomics stroke risk prediction model: metabolomics, epigenomics, genomics, and proteomics inform stroke risk.

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review

Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review

Authors of this article:

Hae Young Yoo1 Author Orcid Image ;   Hyerim Shin1 Author Orcid Image ;   Eun-Jung Kim1 Author Orcid Image ;   Youn-Jung Son1 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Stepanov A, Bogdanov L, Shishkova D, Kutikhin A. Application of artificial intelligence-based tools in experimental and translational cardiology: a review. Russian Journal of Cardiology 2026;31(2S):6901 View
  2. Ardic N, Dinc R. Multi-Omics Integration in Stroke: Neuroinflammatory Endotypes, Immune Cell Crosstalk, and Precision Biomarker Discovery. International Journal of Molecular Sciences 2026;27(13):5984 View
  3. Zhao S, Liu L, Wu J, Long C, Xu J, Huang F, He B, Wu D, Liang Y, Yan C, Fu L, He C, Yuan G. Advances in genetics and multi-omics for ischemic stroke: from pathogenesis to clinical translation. Frontiers in Genetics 2026;17 View