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

Clinical Cancer Research (116) Breast Cancer (291) Innovations and Technology in Cancer Care (532) Decision Support for Health Professionals (1542) Computer-Aided Diagnosis (252) Innovations in Cancer Diagnostic and Decision Support (110)

Published on in Vol 11 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/54625, first published .
Predicting Overall Survival in Patients with Male Breast Cancer: Nomogram Development and External Validation Study

Predicting Overall Survival in Patients with Male Breast Cancer: Nomogram Development and External Validation Study

Predicting Overall Survival in Patients with Male Breast Cancer: Nomogram Development and External Validation Study

Authors of this article:

Wen-Zhen Tang1 Author Orcid Image ;   Shu-Tian Mo1 Author Orcid Image ;   Yuan-Xi Xie2 Author Orcid Image ;   Tian-Fu Wei3 Author Orcid Image ;   Guo-Lian Chen4 Author Orcid Image ;   Yan-Juan Teng1 Author Orcid Image ;   Kui Jia3 Author Orcid Image
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Journals

  1. Xu M, Jiang Z, Liao W, Kang Y, Feng X, Jiang K, Jiang Q, Cong Z, Luo J, Wu L, Shen Y, Wang F. Predicting Postoperative Recurrence Using a Support Vector Machine for Patients With Esophageal Squamous Cell Carcinoma: Machine Learning Modeling Development and Validation Study. JMIR Cancer 2025;11:e68027 View