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NEJM AI Grand Rounds
AI at the Frontlines: Dissecting Clalit’s Roadmap for the Future of Public Health with Noa Dagan and Ran Balicer
Sep 18, 2024
In this engaging conversation, Noa Dagan and Ran Balicer from the Clalit Research Institute share insights into their innovative work with predictive models in healthcare. They discuss leveraging a unique dataset to enhance Hepatitis C screening and how data shaped responses during the COVID-19 pandemic. The duo emphasizes the transformative power of AI in public health, plans for a digital health residency, and the importance of mentorship in emerging public health professionals. With a touch of humor, they even ponder alternative careers and favorite superpowers.
01:11:23
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Quick takeaways
- Clalit Research Institute's use of predictive models significantly improves screening outcomes, identifying high-risk individuals who might otherwise be missed.
- The integration of a vast dataset during COVID-19 demonstrates the transformative potential of comprehensive health data in guiding public health decisions.
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Transformative Screening Through AI
A recent study demonstrated the substantial value of utilizing a comprehensive database to develop a machine learning algorithm aimed at identifying high-risk members for proactive screening. By screening just under 500 individuals deemed at the highest risk, the study uncovered 38 new hepatitis C (HCV) cases that would have otherwise gone unnoticed in a typical screening of over 50,000 individuals. This remarkable 100-fold improvement illustrates a significant shift from traditional public health methods to predictive care, showcasing how AI can revolutionize screening processes and health interventions. This approach symbolizes the progressive evolution of modern public health in the age of artificial intelligence.
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Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode