AI is influencing women’s health in new ways, from fertility to menopause
- On June 20, 2025, experts highlighted how artificial intelligence is transforming women's health by improving diagnosis and personalized care from fertility to menopause.
- This development responds to longstanding issues where many women suffer delayed or missed diagnoses of conditions like endometriosis due to limited data and awareness.
- New AI tools use health records, wearable devices, and genetic data to predict ovulation, identify cancer early, and manage menopause symptoms, integrating biometric patterns without manual input.
- Studies show hormonal fluctuations influence cognition and social attention, while blood test markers like creatinine-to-cystatin C ratio predict muscle decline, linking AI insights to broader health impacts for women.
- These advances suggest growing momentum in femtech innovation, but experts emphasize the need for inclusive data and continued human oversight to ensure equitable and effective women's healthcare.
18 Articles
18 Articles
Menstrual cycle hormone levels influence women’s attention to female faces, brain imaging study finds
Hormonal shifts during the menstrual cycle appear to influence how women process social information. A new fMRI study shows that progesterone enhances attentional control toward female faces by modulating brain activity in key cognitive regions.
We Need Non-Bleeding Cycle Tracking, but Clue Misses the Mark
One of the best period-tracking apps out there, Clue, recently announced a feature that should be groundbreaking for people who don't menstruate but still experience cyclical health changes. The app claims to be the only health app that tracks your cycle even when you don’t bleed. This would mean people who don't have periods due to surgery, hormonal medications, gender transition, or life stages like post-menopause can track their cycles, too.T…
Artificial intelligence-derived retinal age gap as a marker for reproductive aging in women
Reproductive aging impacts women’s health through fertility decline, disease susceptibility, and systemic aging. This study explores the retinal age gap—the difference between predicted retinal age and chronological age—as a novel biomarker for reproductive aging. By developing a Swin-Transformer-based dual-channel transfer learning model with data from 1294 healthy women, we examined associations between the retinal age gap and Anti-Müllerian H…
A report from the University of Cambridge reveals risks of privacy and safety for women using these applications, especially for those seeking pregnancy
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