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Using AI to Help Doctors Save Lives
Feb 15, 2024
Suchi Saria, founder and CEO of Bayesian Health, and a professor at Johns Hopkins, discusses using AI to detect hospital patients at risk of complications. Challenges of integrating AI in healthcare, building trust in real-time information, and potential impact on healthcare market. Building an AI model for sepsis detection and the importance of detailed data. Potential impact of software in detecting sepsis and bed sores. Exploring AI applications and user experience. The need for AI to solve people problems.
39:50
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Quick takeaways
- Using AI can help detect potentially deadly complications in hospital patients, improving treatment timing and patient outcomes.
- Building trust with clinicians and integrating AI into existing healthcare practices are crucial for successful adoption and implementation of AI systems in hospitals.
Deep dives
Using AI to Detect Hospital Patient Complications
Suchi Saria, founder and CEO of Bayesian Health and professor at Johns Hopkins, discusses the challenge of using artificial intelligence (AI) to detect when hospital patients are at risk of potentially deadly complications. The process involves collecting detailed patient data, understanding the clinical processes involved, and building and refining AI models. Saria's company has focused on detecting sepsis, a life-threatening condition, as well as other conditions like pressure ulcers. Studies have shown that the AI system can detect complications earlier, improve treatment timing, and lead to better patient outcomes. The challenge lies in building trust with clinicians and integrating the AI system into existing healthcare practices.
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