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

Machine Learning (2261) Clinical Information and Decision Making (2105) Tools, Programs and Algorithms (417) Decision Support for Health Professionals (1659) Innovations and Technology in Cancer Care (577) Secondary Use of Clinical Data for Research and Surveillance (500) Artificial Intelligence (2399) Cancer Prognosis Models and Machine Learning (86)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73765, first published .
Predicting Lymph Node Metastasis in Rectal Cancer: Development and Validation of a Machine Learning Model Using Clinical Data

Predicting Lymph Node Metastasis in Rectal Cancer: Development and Validation of a Machine Learning Model Using Clinical Data

Predicting Lymph Node Metastasis in Rectal Cancer: Development and Validation of a Machine Learning Model Using Clinical Data

Authors of this article:

Wei Hou1, 2, 3 Author Orcid Image ;   Chuangwei Li1, 2, 3 Author Orcid Image ;   Zhen Wang1, 2, 3 Author Orcid Image ;   Wanqin Wang2, 4 Author Orcid Image ;   Shouhong Wan2, 5 Author Orcid Image ;   Bingbing Zou1, 2, 3 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

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  2. Wu F, Luo C, Zhou S, Peng Z, Ruan G, Yang X, Li S, Huang W, Liu L, Zhou J, Liang B, Li H. Recurrent laryngeal nerve lymph nodes status prediction after neoadjuvant therapy for thoracic esophageal squamous cell carcinoma. Insights into Imaging 2026;17(1) View