Geoff Tison, MD, MPH

HS Asst. Clinical Professor
M_MED-CORE-CARD

Geoff Tison, M.D. M.P.H. is a Cardiologist, Associate Professor in the Division of Cardiology at UCSF and Co-Director of the UCSF Center for Biosignal Research. Dr. Tison earned his Sc.B. in Neuroscience at Brown University and received his M.D. and M.P.H. degrees from the Johns Hopkins Schools of Medicine and Public Health. He completed internal medicine residency at the Johns Hopkins Hospital, and subsequently completed fellowships in clinical cardiology, advanced echocardiography and preventive cardiology at UCSF. He also served as the first UCSF “Digital Cardiology” fellow, where his efforts were focused on validating and improving various digital, mobile and medical-device-based technologies to achieve the greatest impact in clinical care and medical research.

Research Interests: Dr. Tison brings expertise in clinical research, advanced machine learning algorithms and digital health to bear to further his research goals in cardiovascular disease prevention. An expert in machine learning and artificial intelligence as applied to medicine, he obtained formal training in epidemiology, statistical methods, machine learning and clinical research during his tenure at the Johns Hopkins Bloomberg School of Public Health and as a National Institutes of Health T32 scholar. He has led multiple research projects in large cohorts such as the Multi-Ethnic Study of Atherosclerosis and the Women’s Health Initiative. Dr. Tison is an investigator in the UCSF Health eHeart study and leads several clinical research studies at UCSF. Dr. Tison’s current interests include applying machine learning and deep-learning techniques to large-scale electronic health data from heterogeneous sources in order to achieve the goal of personalized cardiovascular prognosis and disease prevention.

Clinical Interests: Dr. Tison is a non-invasive cardiologist with expertise in preventive cardiology and advanced echocardiography, including applications of transesophageal echocardiography in structural interventions such as transcatheter aortic valve replacement.

Publications

Detecting structural heart disease from electrocardiograms using AI.

Nature

Poterucha TJ, Jing L, Ricart RP, Adjei-Mosi M, Finer J, Hartzel D, Kelsey C, Long A, Rocha D, Ruhl JA, vanMaanen D, Probst MA, Daniels B, Joshi SD, Tastet O, Corbin D, Avram R, Barrios JP, Tison GH, Chiu IM, Ouyang D, Volodarskiy A, Castillo M, Roedan Oliver FA, Malta PP, Ye S, Rosner GF, Dizon JM, Ali SR, Liu Q, Bradley CK, Vaishnava P, Waksmonski CA, DeFilippis EM, Agarwal V, Lebehn M, Kampaktsis PN, Shames S, Beecy AN, Kumaraiah D, Homma S, Schwartz A, Hahn RT, Leon M, Einstein AJ, Maurer MS, Hartman HS, Hughes JW, Haggerty CM, Elias P

Foundation models for generalizable electrocardiogram interpretation: comparison of supervised and self-supervised electrocardiogram foundation models.

medRxiv : the preprint server for health sciences

Nolin-Lapalme A, Sowa A, Delfrate J, Tastet O, Corbin D, Kulbay M, Ozdemir D, Noël MJ, Marois-Blanchet FC, Harvey F, Sharma S, Ansari M, Chiu IM, Dsouza V, Friedman SF, Chassé M, Potter BJ, Afilalo J, Elias PA, Jabbour G, Bahani M, Dubé MP, Boyle PM, Chatterjee NA, Barrios J, Tison GH, Ouyang D, Maddah M, Khurshid S, Cadrin-Tourigny J, Tadros R, Hussin J, Avram R

Artificial Intelligence in Cardiovascular Clinical Trials.

Journal of the American College of Cardiology

Cunningham JW, Abraham WT, Bhatt AS, Dunn J, Felker GM, Jain SS, Lindsell CJ, Mace M, Martyn T, Shah RU, Tison GH, Fakhouri T, Psotka MA, Krumholz H, Fiuzat M, O'Connor CM, Solomon SD, Heart Failure Collaboratory