Current Obstetrics and Gynecology Reports

Abstract Purpose of Review This report describes an overview of current applications of artificial intelligence in healthcare with specific focus on uses within women’s health and menopause care. We aim to identify which tools and methods have been applied to menopause diagnosis, symptom management, and treatment personalization, while also reflecting upon the structural and data barriers that prevent equitable use of AI in this domain. Recent Findings As AI has continued to advanced rapidly within healthcare, mature applications such as in drug discovery and diagnostic imaging have shown promise to improve care. Despite this, advancements in menopuase care remain a significant gap: as of 2025, none of the 1,257 FDA-approved AI algorithms focus on menopause diagnosis or treatment. Existing maching learning approaches are limited by data issues such as sparse, inconsistently captured clinical data as well as underrepresentation of large groups of women, partricularly women of color, in research databases. Data missingness disproportionately affects already-underserved populations, meaning application of these AI tools risks amplifying these disparities further. Summary While menopause represents a potential space for development of artificial intelligence solutions, meaningful structural changes to data acquisition and interpretation are required to ensure accurate, impactful, and equitable care.

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Publication Details

Journal
Current Obstetrics and Gynecology Reports
Published
2026-07-30
DOI
https://doi.org/10.1007/s13669-026-00481-1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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Current Obstetrics and Gynecology Reports

Melissa S. Wong, Sarah M. Temkin
Current Obstetrics and Gynecology Reports
Artificial Intelligence in Healthcare and Education
article

Current Obstetrics and Gynecology Reports

Melissa S. Wong, Sarah M. Temkin
article en

Abstract

Abstract Purpose of Review This report describes an overview of current applications of artificial intelligence in healthcare with specific focus on uses within women’s health and menopause care. We aim to identify which tools and methods have been applied to menopause diagnosis, symptom management, and treatment personalization, while also reflecting upon the structural and data barriers that prevent equitable use of AI in this domain. Recent Findings As AI has continued to advanced rapidly within healthcare, mature applications such as in drug discovery and diagnostic imaging have shown promise to improve care. Despite this, advancements in menopuase care remain a significant gap: as of 2025, none of the 1,257 FDA-approved AI algorithms focus on menopause diagnosis or treatment. Existing maching learning approaches are limited by data issues such as sparse, inconsistently captured clinical data as well as underrepresentation of large groups of women, partricularly women of color, in research databases. Data missingness disproportionately affects already-underserved populations, meaning application of these AI tools risks amplifying these disparities further. Summary While menopause represents a potential space for development of artificial intelligence solutions, meaningful structural changes to data acquisition and interpretation are required to ensure accurate, impactful, and equitable care.

Current Obstetrics and Gynecology ReportsVol. 15(1)
Cedars-Sinai Medical Center (US), American Cancer Society (US), Sinai Health System (US)
Cedars-Sinai Medical Center
Gender equality
Openalex Percentile: Top 12%
Artificial Intelligence in Healthcare and Education
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