Seminar Series: Implementation and Evaluation of AI in Real-World Clinical Settings

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The October AI seminar will honor Atul Butte's enduring legacy by showcasing projects built on the computational ecosystem he created at UCSF, including high-impact and widely used tools such as the Information Commons, Wynton, PatientExploreR, SPOKE, and clinical NLP services such as cTAKES-as-a-Service and de-identification pipelines. Atul's work focused on open, rigorous, and collaborative data science with a relentless focus on impact for patients and trainees. We share these projects in gratitude, and with a commitment to carry Atul’s spirit of building bridges between data, discovery, and people. Halloween costumes are highly encouraged!

 

Please email Stephanie Chuc at [email protected] for invite.

 

“From Data to Knowledge: Integrating Clinical and Molecular Data for Predictive Medicine"

Marina Sirota, PhD

Alzheimer’s disease (AD) remains one of the most pressing medical challenges. Recent advances in computational biology and artificial intelligence (AI) together with availability of rich molecular and clinical data, offer new opportunities to address these challenges by integrating molecular, clinical, and systems-level insights. This talk will highlight complementary approaches that illustrate the power of combining real-world clinical data, knowledge networks, and systems pharmacology to advance precision medicine for AD. This work highlights a paradigm shift toward AI-enabled, data-driven strategies that bridge molecular discovery and clinical application, ultimately informing novel therapeutic interventions and improving patient care.

 

“The Future of Evidence-Based Medicine is Data-Driven Medicine: Leveraging Data and AI in the Cancer Clinic"

Julian Hong, MD, MS

The integration of real-world data, artificial intelligence (AI), and clinical informatics has the opportunity to transform oncology, creating new opportunities to improve patient outcomes through data-driven precision medicine. In our recent studies, we work to realize Dr. Butte's vision of “data-driven medicine" and “scalable privilege,” building on our experience in applying artificial intelligence (AI)-directed treatment strategies to mitigate treatment-related toxicities in a randomized controlled trial. We leverage Dr. Butte’s transformative contributions to UCSF infrastructure to advance our efforts in generalizing actionable predictive clinical models, generating real world evidence, and integrating large language models (LLMs). These efforts build a realistic pathway towards realizing broadly accessible, data-driven clinical care.

 

 

About Marina Sirota, PhD

Marina is currently a Professor and the Interim Director at the Bakar Computational Health Sciences Institute at UCSF. Prior to that she has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. She completed her PhD in Biomedical Informatics at Stanford University under the mentorship of Dr. Atul Butte. Dr. Sirota’s research experience in translational bioinformatics spans nearly 20 years during which she has co-authored over 170 scientific publications. Her research interests lie in developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics with a special focus on women’s health.

The Sirota laboratory is funded by NIA, NLM, NIAMS, Pfizer, March of Dimes and the Burroughs Wellcome Fund. As a young leader in the field, she has been awarded the AMIA Young Investigator Award in 2017.  Dr. Sirota also is the founding director of the AI4ALL program at UCSF, with the goal of introducing high school girls to applications of AI and machine learning in biomedicine.

About Julian Hong, MD, MS

Julian is Associate Professor and Medical Director of Radiation Oncology Informatics in the Department of Radiation Oncology, Division of Clinical Informatics and Digital Transformation (DoC-IT), Bakar Computational Health Sciences Institute, and UCSF-UC Berkeley Joint Program in Computational Precision Health. Clinically, he specializes in the treatment of genitourinary malignancies. His research team combines clinical domain knowledge with data science expertise to generate insights from real world data, develop actionable artificial intelligence-based tools, and implement and evaluate the benefit of these advances in patient care.

The Hong lab is funded by the NCI, PCORI, PCF, ASCO Conquer Cancer Foundation, and ASTRO, and Julian is the UCSF co-PI of Weill Cancer Hub West Project IMPACT, which seeks to apply computational approaches to personalize cancer therapy.

Add to Calendar 2025-10-31 20:00:00 2025-10-31 21:00:00 Seminar Series: Implementation and Evaluation of AI in Real-World Clinical Settings The October AI seminar will honor Atul Butte's enduring legacy by showcasing projects built on the computational ecosystem he created at UCSF, including high-impact and widely used tools such as the Information Commons, Wynton, PatientExploreR, SPOKE, and clinical NLP services such as cTAKES-as-a-Service and de-identification pipelines. Atul's work focused on open, rigorous, and collaborative data science with a relentless focus on impact for patients and trainees. We share these projects in gratitude, and with a commitment to carry Atul’s spirit of building bridges between data, discovery, and people. Halloween costumes are highly encouraged!   Please email Stephanie Chuc at [email protected] for invite.   “From Data to Knowledge: Integrating Clinical and Molecular Data for Predictive Medicine" Marina Sirota, PhD Alzheimer’s disease (AD) remains one of the most pressing medical challenges. Recent advances in computational biology and artificial intelligence (AI) together with availability of rich molecular and clinical data, offer new opportunities to address these challenges by integrating molecular, clinical, and systems-level insights. This talk will highlight complementary approaches that illustrate the power of combining real-world clinical data, knowledge networks, and systems pharmacology to advance precision medicine for AD. This work highlights a paradigm shift toward AI-enabled, data-driven strategies that bridge molecular discovery and clinical application, ultimately informing novel therapeutic interventions and improving patient care.   “The Future of Evidence-Based Medicine is Data-Driven Medicine: Leveraging Data and AI in the Cancer Clinic" Julian Hong, MD, MS The integration of real-world data, artificial intelligence (AI), and clinical informatics has the opportunity to transform oncology, creating new opportunities to improve patient outcomes through data-driven precision medicine. In our recent studies, we work to realize Dr. Butte's vision of “data-driven medicine" and “scalable privilege,” building on our experience in applying artificial intelligence (AI)-directed treatment strategies to mitigate treatment-related toxicities in a randomized controlled trial. We leverage Dr. Butte’s transformative contributions to UCSF infrastructure to advance our efforts in generalizing actionable predictive clinical models, generating real world evidence, and integrating large language models (LLMs). These efforts build a realistic pathway towards realizing broadly accessible, data-driven clinical care.     About Marina Sirota, PhD Marina is currently a Professor and the Interim Director at the Bakar Computational Health Sciences Institute at UCSF. Prior to that she has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. She completed her PhD in Biomedical Informatics at Stanford University under the mentorship of Dr. Atul Butte. Dr. Sirota’s research experience in translational bioinformatics spans nearly 20 years during which she has co-authored over 170 scientific publications. Her research interests lie in developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics with a special focus on women’s health. The Sirota laboratory is funded by NIA, NLM, NIAMS, Pfizer, March of Dimes and the Burroughs Wellcome Fund. As a young leader in the field, she has been awarded the AMIA Young Investigator Award in 2017.  Dr. Sirota also is the founding director of the AI4ALL program at UCSF, with the goal of introducing high school girls to applications of AI and machine learning in biomedicine. About Julian Hong, MD, MS Julian is Associate Professor and Medical Director of Radiation Oncology Informatics in the Department of Radiation Oncology, Division of Clinical Informatics and Digital Transformation (DoC-IT), Bakar Computational Health Sciences Institute, and UCSF-UC Berkeley Joint Program in Computational Precision Health. Clinically, he specializes in the treatment of genitourinary malignancies. His research team combines clinical domain knowledge with data science expertise to generate insights from real world data, develop actionable artificial intelligence-based tools, and implement and evaluate the benefit of these advances in patient care. The Hong lab is funded by the NCI, PCORI, PCF, ASCO Conquer Cancer Foundation, and ASTRO, and Julian is the UCSF co-PI of Weill Cancer Hub West Project IMPACT, which seeks to apply computational approaches to personalize cancer therapy. Division of Clinical Informatics and Digital Transformation America/Los_Angeles public