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

Clinical Information and Decision Making (1407) Machine Learning (1465) Secondary Use of Clinical Data for Research and Surveillance (367) Colon and Rectal Cancer (21) Artificial Intelligence (1371) Decision Support for Health Professionals (1185)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44417, first published .
Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study

Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study

Predicting Colorectal Cancer Survival Using Time-to-Event Machine Learning: Retrospective Cohort Study

Authors of this article:

Xulin Yang1 Author Orcid Image ;   Hang Qiu1, 2 Author Orcid Image ;   Liya Wang2 Author Orcid Image ;   Xiaodong Wang3 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

Journals

  1. Yang P, Qiu H, Yang X, Wang L, Wang X. SAGL: A self-attention-based graph learning framework for predicting survival of colorectal cancer patients. Computer Methods and Programs in Biomedicine 2024;249:108159 View
  2. Qi H, Hu Y, Fan R, Deng L. Tab-Cox: An Interpretable Deep Survival Analysis Model for Patients With Nasopharyngeal Carcinoma Based on TabNet. IEEE Journal of Biomedical and Health Informatics 2024;28(8):4937 View
  3. Yang P, Chen W, Qiu H. MMGCN: Multi-modal multi-view graph convolutional networks for cancer prognosis prediction. Computer Methods and Programs in Biomedicine 2024;257:108400 View
  4. Li Q, Geng S, Luo H, Wang W, Mo Y, Luo Q, Wang L, Song G, Sheng J, Xu B. Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy. Signal Transduction and Targeted Therapy 2024;9(1) View
  5. Chen G, Ren Q, Zhong Z, Li Q, Huang Z, Zhang C, Yuan H, Feng Z, Chen B, Wang N, Feng Y. Exploring the gut microbiome’s role in colorectal cancer: diagnostic and prognostic implications. Frontiers in Immunology 2024;15 View