Evidence-led articles on femtech and innovation for women, published in Tulsy Daily by the team building Tulsy AI.
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Digital tools could make egg freezing choices clearer, but population averages are not personal forecasts. New outcome data show what responsible fertility technology should explain.
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New research shows both sides of digital women’s health: wearables may anticipate relevant behaviour, while menstrual tracking can create privacy and interpretation risks.
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An investigational GLP-1 pill produced similar weight-loss results before, during and after menopause. The finding is encouraging, but important evidence gaps remain.
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A urine and vaginal-fluid test may offer a less invasive first step for postmenopausal bleeding. The promise is fewer procedures, not diagnosis without clinical follow-up.
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New imaging and virtual-cell tools could reveal pelvic tissue damage and predict breast cancer drug response. Their clinical value will depend on rigorous validation.
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Menopause technology is advancing faster than the clinical infrastructure around it. Better symptom records could support safer, more individualised care.
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New diagnostic standards could make heart attacks easier to recognise in women. The key advance is not a new device, but more precise interpretation of existing tests.
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New hormone tools promise a closer view of reproductive biology. Environmental exposure research shows why useful interpretation will require context, repeated data and restraint.
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Period tracking could improve recognition and monitoring of PMOS, but useful FemTech must combine longitudinal symptom data with clinical caution and strong privacy.
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Risk-based breast screening and AI models for early puberty show how women’s health is becoming more personalised, while exposing challenges in data, validation and access.
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AI-supported platforms are connecting menopause, sleep, weight and metabolic care. Their value will depend on female-specific evidence, clinical oversight and privacy.
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