Geoffrey Huang Tison MD
Clinical Fellow, Medicine, UCSF School of Medicine
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505 Parnassus AveSan Francisco, CA 94131
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Education & Training
University of California (San Francisco)Fellowship, Cardiovascular Disease, 2016
Johns Hopkins UniversityResidency, Internal Medicine, 2009 - 2012- Johns Hopkins University School of MedicineClass of 2009
Certifications & Licensure
CA State Medical License 2012 - 2025
American Board of Internal Medicine Internal Medicine- American Board of Internal Medicine Cardiovascular Disease
Publications & Presentations
PubMed
- Association of Extracoronary Calcification and Incident Heart Failure in the Multiethnic Study of Atherosclerosis (MESA).Sandeep Brar, Rahul Goli, Joshua P Barrios, Michael J Blaha, Sina Kianoush
JACC. Heart Failure. 2025-03-26 - Foundation models for generalizable electrocardiogram interpretation: comparison of supervised and self-supervised electrocardiogram foundation models.Alexis Nolin-Lapalme, Achille Sowa, Jacques Delfrate, Olivier Tastet, Denis Corbin
Medrxiv. 2025-03-05 - Association Between Elevated Total Homocysteine and Heart Failure Risk in the Multi-Ethnic Study of Atherosclerosis Cohort.Amy B Karger, Sarah O Nomura, Weihua Guan, Parveen K Garg, Geoffrey H Tison
Journal of the American Heart Association. 2025-03-04
Journal Articles
- Finding New Meaning in Everyday Electrocardiograms—Leveraging Deep Learning to Expand Our Diagnostic ToolkitGeoffrey Tison, MD, JAMA Cardiology
- Identifying Heart Failure Using EMR-Based AlgorithmsMark J Pletcher, Geoffrey H Tison, Jeffrey E Olgin, Shannon M Dunlay, ScienceDirect
Press Mentions
Using AI in Electrocardiogram Analysis Can Improve Diagnosis and Treatment of Hypertrophic CardiomyopathyMarch 7th, 2022- 'We're in the Messy Adolescence of This Experience': How the Annual Physical Visit Is Shifting to VirtualSeptember 7th, 2021
- AI Uncovers Occult Long QT SyndromeFebruary 10th, 2021
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Grant Support
- A physiologically-focused approach to training multi-modality AI algorithms in medicineUNIVERSITY OF CALIFORNIA, SAN FRANCISCO2023–2026
- Developing a platform for deep phenotyping of heart failure with preserved ejection fraction using raw, widely-available, multi-modality data and artificial intelligence algorithmsUNIVERSITY OF CALIFORNIA, SAN FRANCISCO2022–2025
- Developing a platform for deep phenotyping of heart failure with preserved ejection fraction using raw, widely-available, multi-modality data and artificial intelligence algorithmsUNIVERSITY OF CALIFORNIA, SAN FRANCISCO2022–2025
- Developing a platform for deep phenotyping of heart failure with preserved ejection fraction using raw, widely-available, multi-modality data and artificial intelligence algorithmsUNIVERSITY OF CALIFORNIA, SAN FRANCISCO2022–2025
Professional Memberships
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