Wearable AI in Clinical Decisions

Agenda:

9:00 - 9:30 am
“Scalable approach to consumer wearable postmarket surveillance: Development and validation study”
Ben Viggiano, PhD, Doctoral Student in Biomedical Informatics, Stanford University
Krishna Pundi, MD, Cardiac Electrophysiologist, Palo Alto VA Health Care System; Clinical Instructor, Stanford University

9:30 - 10:00 am
“Exploring the potential of wearable AI in clinical care” 
Arjun Mahajan, MD student, Harvard and editorial fellow, Nature Portfolio Journal
Dylan Powell, PhD, Physiotherapist, Assistant Professor (Lecturer) Public Health & Innovation, News and Views Editor, Nature npj Digital Medicine

Abstract:

“Scalable approach to consumer wearable postmarket surveillance: Development and validation study”
Consumer wearables capable of rendering prediagnoses, such as for atrial fibrillation (AF), have the potential to influence downstream clinical decision-making. However, postmarket surveillance has been limited by the absence of codified indicators of wearable use in electronic health records (EHRs). In this talk, we demonstrate a novel approach to address this gap using a weak supervision-based framework to identify wearable-driven AF prediagnoses from clinical notes. Leveraging data programming via labeling functions and the Snorkel framework, we constructed a labeler model to probabilistically annotate notes and fine-tuned a Clinical-Longformer classifier. Using this approach, we were able to study the clinical characteristics of individuals with AF prediagnoses, their subsequent healthcare use, and clinical outcomes in a real-world cohort. This presentation demonstrates the feasibility and utility of EHR-based surveillance for consumer health technologies.

“Exploring the potential of wearable AI in clinical care”  
This presentation will explore the transformative potential of wearable AI technologies in clinical care, highlighting how these intelligent systems may enhance patient safety and support improved decision-making across diverse healthcare settings. Drawing on recent advancements in digital biomarkers and AI-enabled wearables, we will examine practical applications and discuss the challenges and opportunities for integrating these innovations into routine clinical practice.