Overview
UCSF is working to leverage the power of AI with the goal of improving human health.
Advancing knowledge to improve human health
Several AI initiatives are already underway:
- A novel brain implant and digital avatar enabling a stroke survivor to communicate through facial expressions for the first time in nearly two decades.
- An AI system that designs synthetic enzymes from the ground up, in addition to a multitude of research initiatives across the molecular, cellular and tissue scales, which could ultimately lead to new precision therapies.
- New education programs like the Computational Precision Health PhD, which merges machine learning/AI with clinical practice and equity, in addition to an abundance of training opportunities, which aim to strengthen UCSF's expertise in clinical AI.
- Efforts to reduce clinician burnout and recenter the "human touch" for patients including the evaluation of an AI-powered scribe.
- Improving responsiveness to patient messages and the readability of replies by offering providers AI-generated first drafts of responses.
- Multiple programs that enhance diagnostic imaging and provide early clinical risk alerting.
- Investments in the infrastructure needed to support an AI-enabled future.
- A curated central database of over 9 million patients treated in the last decade from across the UC health system.
UCSF in the national conversation
UCSF’s thought leaders are shaping the conversation on AI in health care:
- Atul Butte, MD, PhD, Director of the Bakar Computational Health Sciences Institute, sees large language models as instrumental in democratizing oncology care, enabling high-quality care delivery to patients everywhere, regardless of their access to top-tier cancer centers.
- Sara Murray, MD, MAS, Associate Professor of Medicine and Chief Health AI Officer for UCSF Health, believes AI could support “keyboard liberation” for clinicians, potentially alleviating clinician burnout by saving time on administrative tasks.
- Bob Wachter, MD, Chair of the Department of Medicine, is optimistic that generative AI can deliver meaningful improvements in health care more rapidly than previous technologies and is hopeful that it can support everything from scheduling to clinical documentation and eventually diagnostic assistance.
- Ida Sim, MD, PhD, Professor of Medicine and Director of the UCSF UC Berkeley Joint Program in Computational Precision Health, thinks AI will not replace clinicians, but augment the work they do. That’s why Sim argues that it is incumbent on clinicians and health care leaders to be part of the conversation now and provide input on these technologies.
- Cristy Boscardin, PhD, Professor in the Department of Medicine and Department of Anesthesia and Perioperative Care, urges educators to increase their AI literacy and to become stewards of AI literacy so they can foster social responsibility and ethical awareness around the use of AI with learners.
- Sharmila Majumdar, PhD, Professor in the Departments of Bioengineering and Therapeutic Sciences, Orthopedic Surgery at UCSF and Bioengineering at UC Berkeley, is leading efforts to harness AI to read medical scans such as MRIs and help spot nuances or connections that even the most highly trained clinical professionals might miss. She thinks AI can help diagnose complex, heterogeneous disease including lower back pain.
- Several leaders at UCSF including Keith Yamamoto, PhD, Special Adviser to the Chancellor for Science Policy and Strategy and Director of UCSF’s Precision Medicine Program, Chancellor Sam Hawgood, MBBS, and Ida Sim, MD, PhD, are leading efforts to better understand and address biases in artificial intelligence. At a recent workshop, Toward Algorithmic Justice in Precision Medicine, they discussed and put forward recommendations for an equitable approach to data collection, processing and decision making.