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

Digital Health Reviews (3836) Respiratory Medicine (224) mHealth for Data Collection and Research (1777) Decision Support for Health Professionals (2340) Innovations and Technology in Cancer Care (706)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/93892, first published .
Doctor analyzing lung scan with holographic medical data and charts.

Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non–Small Cell Lung Cancer: Systematic Review and Meta-Analysis

Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non–Small Cell Lung Cancer: Systematic Review and Meta-Analysis

Authors of this article:

Ziqi Jiang1 Author Orcid Image ;   Yuan Xu1 Author Orcid Image ;   Shuyu Jia2 Author Orcid Image ;   Hongsheng Liu1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Kan W, Pei H, Zhang M. Same-Patient, Same–Time Point Evidence for Radiomics Benchmarking. Journal of Medical Internet Research 2026;28:e110058 View
  2. Jiang Z, Xu Y, Jia S, Liu H. Authors’ Reply: Clarifying the Comparative Interpretation and Clinical Implications of Radiomics-Based AI for Pathological Response Prediction. Journal of Medical Internet Research 2026;28:e110607 View