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Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72424, first published .
Doctor in mask discusses patient results on computer screen

A Machine Learning Approach to Predicting Mortality Risk in Chemotherapy-Treated Lung Cancer: Machine Learning Model Development and Validation

A Machine Learning Approach to Predicting Mortality Risk in Chemotherapy-Treated Lung Cancer: Machine Learning Model Development and Validation

Journals

  1. Zou Y, Zhu J, Cheng J, Yan J, Dai B, Han J, Guo J. Multi-source data-driven machine learning for lung cancer: diagnosis, treatment, and prognosis. Intelligent Opto-Electronics 2026;2(2):260006 View
  2. Liu L, Zuo P, Yu C, Shen X, Luo B, Zhang S, Cao T, Zhou Y, Hu K, Cai Y. Development and external validation of machine learning models for predicting mortality in patients with lung cancer: a multicenter retrospective cohort study. Scientific Reports 2026;16(1) View

Conference Proceedings

  1. Ghaleb M, ElSmahey M, Elsokkary H, Hamdy N. 2026 IEEE International Conference on Smart Sustainable Systems for Computer and Engineering Applications (3SCEA). SOX2OT as a Novel Prognostic Biomarker and Therapeutic Target in Colorectal Cancer View