Michael Scheid, PhD

Michael Scheid is an Assistant Investigator and Senior Biomedical Engineer at the Feinstein Institutes for Medical Research, and lead author of the division's work on predicting in-hospital patient deterioration from continuous wearable biosensor data. His research, published in Nature Communications (2025), demonstrates a deep learning approach that predicts clinical deterioration up to 17 hours in advance, achieving 81.8% accuracy in identifying unplanned ICU transfers and critical outcomes. He holds an NIH Research Specialist Award (R50) from the National Library of Medicine to scale clinical wearable foundation models for the detection of in-hospital deterioration. His additional work includes clinical alert systems for early detection of decline and analysis of ICD remote transmissions for atrial fibrillation prediction.