DPhil student
Research groups
Colleges
Ben Omega Petrazzini
BSc
DPhil student
Global cardiovascular health and artificial intelligence
Biography
After my BS in Biology at Uruguay’s Universidad de la Republica (UdelaR), I joined The Icahn School of Medicine at Mount Sinai to study cardiovascular disease (CVD) genetics and prediction using artificial intelligence (AI).
Now, as a DPhil student, I am studying the use of AI for individualized CVD risk estimations. My goal is to develop a tool to accurately predict CVD risk in any country using a simple blood test. Such a tool would enable CVD care outside hospitals with greater benefits for marginalized populations with limited access to healthcare and high CVD burden.
My work is co-supervised by Prof. Rahimi (Oxford), Dr. Rao (Oxford) and Prof. Di Angelntonio (Cambridge), and funded by the Clarendon Fund and Uruguay’s Agencia Nacional de Investigacion e Innovacion.
Additionally, I serve as the 2024/2025 Graduate Director of Innovation and Entrepreneurship at Reuben College.
Key publications
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Coronary Risk Estimation Based on Clinical Data in Electronic Health Records
Journal article
Petrazzini BO. et al, (2022), Journal of the American College of Cardiology, 79, 1155 - 1166
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Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease
Journal article
Petrazzini BO. et al, (2024), Nature Genetics, 56, 1412 - 1419
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Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts
Journal article
Forrest IS. et al, (2023), The Lancet, 401, 215 - 225
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Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications
Journal article
Duffy Á. et al, (2024), Nature Genetics, 56, 51 - 59
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Prediction of recessive inheritance for missense variants in human disease
Preprint
Petrazzini BO. et al, (2021)
Recent publications
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Expanding drug targets for 112 chronic diseases using a machine learning-assisted genetic priority score
Journal article
Chen R. et al, (2024), Nature Communications, 15
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Comparison of blood-based liver fibrosis scores in the Mount Sinai Health System, MASLD Registry, and NHANES 2017–2020 study
Journal article
Chen R. et al, (2024), Hepatology Communications, 8
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Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease
Journal article
Petrazzini BO. et al, (2024), Nature Genetics, 56, 1412 - 1419
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Muesli Intake May Protect Against Coronary Artery Disease
Journal article
Park JK. et al, (2024), JACC: Advances, 3, 100888 - 100888
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Prediction of Venous Thromboembolism in Diverse Populations Using Machine Learning and Structured Electronic Health Records
Journal article
Chen R. et al, (2024), Arteriosclerosis, Thrombosis, and Vascular Biology, 44, 491 - 504