LEVY Health’s Vision for AI-Based Clinical Decision Support in Women’s Health
We’re at the point where it’s not “if” the AI will be implemented but “how” and for which use case– and increasingly how to scale efficiently.
On the clinical side, higher-risk, higher-reward AI tools – like those used for early detection, diagnostics, or predictive analytics – are gaining traction. These innovations are transformative but require careful consideration, especially when clinical decision-making is involved. Some fall under FDA oversight, while others do not – a topic we’ll revisit when discussing regulation.
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Clinical Decision Support
AI-based Clinical Decision Support Systems (CDSS) go beyond traditional rule-based tools by using machine learning to detect patterns in patient data and deliver tailored recommendations. These systems can process vast amounts of medical literature, clinical guidelines, and patient histories at once—a powerful advantage when dealing with complex or under-researched conditions.
Why Women’s Health Needs AI-CDSS
Conditions like cardiovascular disease, bone and brain health, autoimmune and metabolic disorders often affect women differently and disproportionately compared to men. Yet, many providers lack training in how these diseases present in women. AI-based CDSS can flag atypical symptoms, suggest differential diagnoses, and analyze large datasets, including hormonal patterns and genetics, to generate personalized guidance.
Take cardiovascular disease: it’s the leading cause of death for U.S. women and closely tied to age-related estrogen decline. Closing the gender gap in care could boost the U.S. economy by $28 billion annually by 2040.
Our Vision at LEVY Health
AI quality relies on both data volume and quality. In women’s health, data are often unstructured and incomplete. The bigger issue, however, is what can be collected—over 80% of endocrine disorders are undiagnosed or diagnosed late, largely due to gaps in diagnostic training and guidance.
LEVY Health starts by educating providers on what tests to order and when. This structured data then feeds into larger models – either existing or co-developed with our partners. Over time, we build rich, longitudinal datasets to analyze how biomarkers, symptoms, and treatment outcomes connect to long-term disease risk.
Join Our Ecosystem
We’re looking to collaborate with:
- Innovators building similar tools
- Experts in AI/ML and women’s health
- Health systems aiming to lead in this space
- Clinicians piloting AI in practice
- Anyone with a superpower to contribute
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Beyond the Buzz: LEVY Health’s Vision for AI-Based Clinical Decision Support in Women’s Health
