Dr. Travis Zack, Chief Medical Officer at medical AI platform OpenEvidence, is helping to transform how AI can boost patient care. As an Assistant Professor of Hematology/Oncology at the University of California, San Francisco’s Helen Diller Family Comprehensive Cancer Center, Zack focuses on natural language models and how these tools can extract insights from clinician notes beyond the numerical values that have traditionally been easy to curate. Those detailed reports are imperative to patient care, identifying everything from tests doctors want ordered, to side effects and sensations, such as nausea following chemotherapy, that can affect cancer patients’ treatment.
A study conducted at UCSF in 2024 put AI to the test in just these ways. The results indicated that machine learning could reduce the time oncologists spent accurately reviewing patient records from upwards of two hours to as little as 15 minutes. The study also found that AI flagged tests that needed ordering, helping ensure that “patients progressed to treatment in a timelier manner,” Zack said.
Merging AI tools within electronic health data and making it workable for clinicians has been of interest to Zack for many years. Capturing these “nuances,” through AI has been “really challenging historically,” he said in 2025.
Zack’s early research in oncology dovetailed with his interest in machine learning, leading to his co-authoring several studies that bridged the two fields, including the role of large language models in clinical approaches to cancer therapy. Other studies have explored ways to adapt natural language processing within medical reporting.
Zack earned his BA from the University of California, Berkeley, his Ph.D. in Biophysics from Harvard University, and his M.D. from Harvard Medical School. Zack completed his residency at UCSF, where he continued as a Fellow in Hematology/Oncology, and also held a Fellowship at HemOnc.org.
Please join us in welcoming Dr. Zack to our growing DOC 2026 Faculty.