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

Digital Health Reviews (1747) Cancer Prognosis Models and Machine Learning (69) Machine Learning (2102) Artificial Intelligence (2169)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73528, first published .
Performance of Machine Learning in Diagnosing KRAS (Kirsten Rat Sarcoma) Mutations in Colorectal Cancer: Systematic Review and Meta-Analysis

Performance of Machine Learning in Diagnosing KRAS (Kirsten Rat Sarcoma) Mutations in Colorectal Cancer: Systematic Review and Meta-Analysis

Performance of Machine Learning in Diagnosing KRAS (Kirsten Rat Sarcoma) Mutations in Colorectal Cancer: Systematic Review and Meta-Analysis

Authors of this article:

Kaixin Chen1 Author Orcid Image ;   Yin Qu1 Author Orcid Image ;   Ye Han1 Author Orcid Image ;   Yan Li2 Author Orcid Image ;   Huiyan Gao3 Author Orcid Image ;   De Zheng1 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Sun Y, Li B, Ju C, Hu L, Sun H, An J, Kim T, Bu Z, Shi Z, Liu J, Liu Z. Predictive Performance of Radiomics-Based Machine Learning for Colorectal Cancer Recurrence Risk: Systematic Review and Meta-Analysis. JMIR Medical Informatics 2025;13:e78644 View
  2. Mirlohi M, Yousefi T, Razaviyan J, Nomiri S, Pishbin E, Shabani-Rad M, Ahmadian M, Salami S. Advances and Challenges in KRAS Mutation Detection and Clinical Implications. Cancers 2025;18(1):31 View