Artificial intelligence in gynecopathology: advances, challenges and perspectives

Artificial intelligence (AI) has already been studied not only in histological subtypes between benign and malignant tumors, but also for prognosis and prediction for therapeutic purposes, focusing on molecular alterations and assessment of the tumor microenvironment. This is a comprehensive review to address the current landscape of AI’s contribution in gynecological pathology to improve diagnostic accuracy, streamline analysis, and standardize histopathological evaluation. This review also provides evidence on the implementation of AI in this field of Pathology, with emphasis on three anatomopathological domains: endometrium, ovary, and cervix.

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Publication Details

Journal
Surgical and Experimental Pathology
Published
2026-04-10
DOI
https://doi.org/10.1186/s42047-026-00234-7
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence in gynecopathology: advances, challenges and perspectives

Patrícia Barreto, Rozany Mucha Düfloth, Rafael Bispo Paschoalini, Janaína Nagel et al.
Surgical and Experimental Pathology
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Artificial intelligence in gynecopathology: advances, challenges and perspectives

Patrícia Barreto, Rozany Mucha Düfloth, Rafael Bispo Paschoalini, Janaína Nagel, Isabela C. Watanabe, Camila Sampaio Tomé Veloso-de-Araújo, Débora Maíra Barros Luz, Vinicius Barros Figueiredo, Ana Cristina Caldeira, Lívia Ribeiro Gondim
article en

Abstract

Artificial intelligence (AI) has already been studied not only in histological subtypes between benign and malignant tumors, but also for prognosis and prediction for therapeutic purposes, focusing on molecular alterations and assessment of the tumor microenvironment. This is a comprehensive review to address the current landscape of AI’s contribution in gynecological pathology to improve diagnostic accuracy, streamline analysis, and standardize histopathological evaluation. This review also provides evidence on the implementation of AI in this field of Pathology, with emphasis on three anatomopathological domains: endometrium, ovary, and cervix.

Surgical and Experimental PathologyVol. 9(1)
D’Or Institute for Research and Education (BR)
Good health and well-being
Openalex Percentile: Top 16%
AI in cancer detection
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