Building on a Legacy of Actionable Data Science in Medicine — Honoring a Unique Leader and his Team
AI in medicine is one of the most fascinating frontiers because its applications directly affect patient outcomes. The computational health data scientists at UCSF are among the leaders shaping how artificial intelligence is responsibly developed and applied in real-world care — where innovation meets impact. Dr. Atul Butte, who tragically passed away last summer after a long battle with cancer, mentored this team. They gathered on October 31, 2025 in Star Trek-themed Halloween costumes to share reflections on his impact on their work, while providing exciting updates, during the monthly UCSF AI Seminar Series.
This heartfelt event was hosted by the Bakar Computational Health Sciences Institute (BCHSI), UCSF Division of Clinical Informatics and Digital Transformation (DoC-IT), UC Berkeley — UCSF Computational Precision Health Program, and UCSF Department of Epidemiology and Biostatistics.
Key Takeaways
- Start with the question — meaningful AI begins with the problem, not the tool.
- Validate with a clinical simulation — models must prove their value before implementation.
- Navigate thoughtfully — success requires diligence, awareness, and collaboration to avoid misinformed or premature applications of AI.
A Celebration of Vision, Collaboration, and Impact
The October UCSF AI Seminar brought together faculty, clinicians, and data scientists to honor the legacy of Dr. Atul Butte, whose pioneering work defined UCSF's modern approach to data-driven medicine. Held on Halloween, the event blended reflection and good humor: attendees came dressed in Star Wars and other costumes, while a photo of Atul — remembered fondly as a Star Trek fan — set a warm, personal tone.
The seminar showcased the extraordinary progress being made in applying AI to two of medicine's greatest challenges: Alzheimer's disease and cancer. Featured speakers Marina Sirota, PhD, and Julian Hong, MD, MS — both protégés of Dr. Butte — shared how UCSF continues to build on his vision, bridging computation, collaboration, and clinical impact.
Using AI to Tackle Alzheimer's Disease
Marina Sirota, PhD, opened the seminar with "From Data to Knowledge: Integrating Clinical and Molecular Data for Predictive Medicine." She discussed how AI and molecular data can be used to better understand and treat Alzheimer's disease (AD) — a condition that remains difficult to diagnose early and challenging to treat effectively.
Her research combines computational biology, AI, and large-scale molecular data to uncover new treatment targets and accelerate precision medicine approaches. By integrating real-world clinical data and knowledge networks, her team is helping bridge the gap between discovery and care.
Applying AI to Help Cancer Patients and Advance Care
Julian Hong, MD, MS, followed with "The Future of Evidence-Based Medicine is Data-Driven Medicine: Leveraging Data and AI in the Cancer Clinic." He described how his team uses real-world data and AI tools to improve cancer care, work that became especially urgent during and after the COVID-19 pandemic.
Julian's research builds on Dr. Butte's vision of data-driven medicine — applying AI-guided strategies to reduce treatment-related toxicities and improve patient outcomes.