AI for Women's Health: Framework and Focus Areas
AI for women's health is an open challenge that needs to be addressed by cross-disciplinary efforts. There is an urgent need to establish a new type of collaboration that focuses on integrating and adopting AI methods in healthcare to bridge the gap between the aspiration to apply AI across all aspects of women's health and its practical adoption in everyday clinical practice. This is particularly important for women's health where we know there have been significant lags in finding innovative ways to manage prevalent and burdensome health issues that are experienced proportionately more or only by females across their life courses. This position paper will present our initial development including a comprehensive framework, a high-level methodology and main focus areas of advanced AI for Women's Health. The research aims to support women's health services worldwide by providing new tools and novel applications to improve women's health system efficiency and personalized medicine.
Authors
- Kezhi Lu (ORCID: https://orcid.org/0000-0003-4979-5097)
- Angela J Dawson (ORCID: https://orcid.org/0000-0003-0926-2202)
- Guodong Long (ORCID: https://orcid.org/0000-0003-3740-9515)
- Fahimeh Ramezani (ORCID: https://orcid.org/0000-0002-0368-321X)
- Deborah J. Fox (ORCID: https://orcid.org/0000-0002-8032-8633)
- Debra Anderson (ORCID: https://orcid.org/0000-0001-8996-9624)
- Kathleen Baird (ORCID: https://orcid.org/0000-0003-0142-6962)
- Susan Morton (ORCID: https://orcid.org/0000-0002-2231-7020)
- Kairui Guo (ORCID: https://orcid.org/0000-0003-1570-314X)
- Zelia Soo (ORCID: https://orcid.org/0009-0005-3058-5390)
- Jie Lü (ORCID: https://orcid.org/0000-0003-0690-4732)
Institutions
- University of Technology Sydney (AU)
Publication Details
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1145/3701716.3718981
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00