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

Digital Health Reviews (1807) Clinical Information and Decision Making (2051) Imaging Informatics (326) Artificial Intelligence (2315) Obstetrics, Gynecology, and Reproductive Medicine (341) Cancer Prognosis Models and Machine Learning (78) Innovations in Cancer Diagnostic and Decision Support (120) Medical imaging (129)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71091, first published .
Imaging-Based AI for Predicting Lymphovascular Space Invasion in Cervical Cancer: Systematic Review and Meta-Analysis

Imaging-Based AI for Predicting Lymphovascular Space Invasion in Cervical Cancer: Systematic Review and Meta-Analysis

Imaging-Based AI for Predicting Lymphovascular Space Invasion in Cervical Cancer: Systematic Review and Meta-Analysis

Authors of this article:

Lizhen She1 Author Orcid Image ;   Yunfeng Li1 Author Orcid Image ;   Hongyong Wang1 Author Orcid Image ;   Jun Zhang1 Author Orcid Image ;   Yuechen Zhao1 Author Orcid Image ;   Jie Cui1 Author Orcid Image ;   Ling Qiu1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Shimada Y, Harada K, Kudo Y, Park J, Matsubayashi J, Taguri M, Ikeda N. Prediction of Lymphovascular Invasion in Early–Stage Lung Adenocarcinoma Using Artificial Intelligence–Based Radiomics. Cancers 2025;17(24):3998 View
  2. Gayathri R, Thilagavathy R. CCSA-RF enhanced lightweight multi-scale CNN framework for robust lung cancer classification. Intelligence-Based Medicine 2026;13:100363 View
  3. Li Y, Zhao K, Wu J. Machine Learning in Left Ventricular Hypertrophy Detection: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2026;28:e76637 View