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Next-Gen Clinical Monitoring: Predicting Inpatient Decline with AI-Driven Alerts
Manage episode 521309603 series 3703564
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Host: Brian P. McDonough, MD, FAAFP
Guest: Theodoros Zanos, PhD
An artificial intelligence (AI)-driven clinical alert model has the potential to reshape inpatient care by detecting early signs of deterioration an average of 17 hours before adverse events occur. Dr. Brian McDonough sits down with Dr. Theodoros Zanos, to learn more about how his team combined continuous data from clinical wearables with advanced machine learning to enable early risk detection in the medical-surgical setting. Dr. Zanos leads the Division of Health AI and is an Associate Professor of Medicine at the Feinstein Institutes for Medical Research and the Zucker School of Medicine at Hofstra University/Northwell Health.
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Guest: Theodoros Zanos, PhD
An artificial intelligence (AI)-driven clinical alert model has the potential to reshape inpatient care by detecting early signs of deterioration an average of 17 hours before adverse events occur. Dr. Brian McDonough sits down with Dr. Theodoros Zanos, to learn more about how his team combined continuous data from clinical wearables with advanced machine learning to enable early risk detection in the medical-surgical setting. Dr. Zanos leads the Division of Health AI and is an Associate Professor of Medicine at the Feinstein Institutes for Medical Research and the Zucker School of Medicine at Hofstra University/Northwell Health.
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