Artificial Intelligence for Genetic Cancer Risk Assessment in Gynecologic Oncology: A Review of the Current Landscape and Future Directions.

Journal: Clinical obstetrics and gynecology
Published Date:

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.

Authors

  • Roxanna Haghighat
    Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, Weill Cornell Medicine, NewYork-Presbyterian Hospital, New York, NY.
  • Sarah R Levi
    Weill Cornell Medicine, New York, NY.
  • Melissa K Frey
    Weill Cornell Medicine, New York, NY.

Keywords

No keywords available for this article.