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

Digital Health Reviews (1758) Clinical Information and Decision Making (1957) Imaging Informatics (309) Artificial Intelligence (2197) Computer-Aided Diagnosis (259) Obstetrics, Gynecology, and Reproductive Medicine (335) Theme Issue: Reproductive Informatics (63) Innovations in Cancer Diagnostic and Decision Support (114) Innovations and Technology for Cancer Prevention and Screening (204)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66530, first published .
Diagnosis Test Accuracy of Artificial Intelligence for Endometrial Cancer: Systematic Review and Meta-Analysis

Diagnosis Test Accuracy of Artificial Intelligence for Endometrial Cancer: Systematic Review and Meta-Analysis

Diagnosis Test Accuracy of Artificial Intelligence for Endometrial Cancer: Systematic Review and Meta-Analysis

Authors of this article:

Longyun Wang1 Author Orcid Image ;   Zeyu Wang1 Author Orcid Image ;   Bowei Zhao1 Author Orcid Image ;   Kai Wang1 Author Orcid Image ;   Jingying Zheng2 Author Orcid Image ;   Lijing Zhao1 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Li R, Zou K, Ma Q, Liu Y, Wang X, Huang W, Gao S, Yang X. Deep learning-based automated detection of endometrioid endometrial carcinoma in histopathology. Frontiers in Oncology 2026;15 View