AI for Women's health: Shaping a Healthier Future

Their collaborative paper titled “AI for Women’s Health: Framework and Focus Areas” provides cross-disciplinary insights in integrating and adopting AI methods to the area of women’s health.

Prof Dawson opened the session with her talk, “AI for Women’s Health: The Health Perspective”. This provided an overview of women’s healthcare needs across a woman’s lifespan, offering priority focus areas where AI could contribute to mitigating these problems.

Prof Lu presented, “AI for Women’s Health: Framework and Methodology” which explored the potential of cutting-edge AI methods such as transfer learning, concept drift, and fuzzy learning, that are well-suited to the dynamic and complex problems raised by Prof Dawson. Lastly, Dr Guo’s talk, “AI-Driven Genomic Insights in Women’s Health: Case Studies in IVF, Endometriosis, and Stroke” showcased real-life examples of how the AAII have utilised the AI algorithms discussed by Prof Lu in the focus areas of IVF, endometriosis, and stroke.

This session marks an important milestone in an ongoing collaboration between the AAII and the UTS Faculty of Health, which began earlier this year.