Artificial Intelligence for Genetic Cancer Risk Assessment in Gynecologic Oncology

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Authors: Roxanna Haghighat, S. Levi, Melissa K. Frey
Cited by: 0
References: 76

Abstract

Hereditary cancer syndromes are associated with up to 25% of ovarian and 5% of endometrial cancers, yet rates of genetic testing and counseling remain low. Artificial intelligence (AI) offers new opportunities to streamline risk assessment, enhance gene variant interpretation, and expand access to genetic counseling. This narrative review synthesizes current evidence on AI applications in gynecologic cancer genetic risk assessment, including chatbot-based risk assessment, natural language processing of electronic records, and machine-learning approaches to variant classification. We highlight key challenges, including data bias, privacy, and implementation barriers, and outline future directions for AI technologies in gynecologic cancer genetic risk assessment.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education BRCA gene mutations in cancer AI in cancer detection

Publication details

Journal / source
Clinical Obstetrics & Gynecology
Volume
69
Issue
1
Pages
36–44
Publication date
6 January 2026
Language
EN