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

General Articles on Innovation and Technology in Public Health (52) Colon and Rectal Cancer (17) Cancer Epidemiology, Cancer Surveillance and Infodemiology (67) Clinical Cancer Research (71) Innovations and Technology in Cancer Care (400)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41999, first published .
Comorbidity Patterns in Patients Newly Diagnosed With Colorectal Cancer: Network-Based Study

Comorbidity Patterns in Patients Newly Diagnosed With Colorectal Cancer: Network-Based Study

Comorbidity Patterns in Patients Newly Diagnosed With Colorectal Cancer: Network-Based Study

Authors of this article:

Hang Qiu1, 2 Author Orcid Image ;   Liya Wang1 Author Orcid Image ;   Li Zhou3 Author Orcid Image ;   Xiaodong Wang4 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) 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