D24AC00253

Recent advances in machine learning in particular deep neural networks (DNN) and large language models (LLM) will transform many aspects of healthcare and medicine.

While current AI technology is suitable for automating some repetitive clinical tasks, significant technical challenges remain in solving critical and high payoff problems in the domains of patient and disease management.

This project is focused on the design and implementation of AI based clinical decision support systems for personalized treatment and management recommendations.

The research spans 1) AI foundations problems in trustworthy medical AI such as integrating medical domain knowledge in learning models effectively, making recommendations of AI algorithms explainable to clinicians, and establishing worst case safety guarantees; 2) AI systems infrastructure to facilitate development of explainable models suitable for integration into clinician workflows; and 3) AI use cases representative clinical challenges that span inpatient and outpatient use cases including prevention of in hospital cardiac arrest, early integration of palliative care with cancer directed therapy, and timely diagnosis and intervention for sepsis.

Trustees Of The University Of Pennsylvania

THE FOUR INITIAL FOCUS AREAS ARE(1) HEALTH SCIENCE FUTURES(2) SCALABLE SOLUTIONS(3) PROACTIVE HEALTH(4) RESILIENT SYSTEMS

93.384 - ADVANCED RESEARCH PROJECTS AGENCY for HEALTH (ARPA-H)

Interior Business Center (IBC) [DOI]

Philadelphia, Pennsylvania United States

County-Wide

D-AQD-FA-24-008