Dr. Aristotelis Tsirigos on Pitt HexAI

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Health and Explainable AI Podcast

Pitt HexAI Lab and the Computational Pathology and AI Center of Excellence

34 episodes

1 day ago

The Health and Explainable AI podcast is a collaborative initiative between the Health and Explainable AI (HexAI) Research Lab in the Department of Health Information Management at the School of Health and Rehabilitation Sciences, and the Computational Pathology and AI Center of Excellence (CPACE), at the University of Pittsburgh School of Medicine. Led by Ahmad P. Tafti, Hooman Rashidi and Liron Pantanowitz, the podcast explores the transformative integration of responsible and explainable artificial intelligence into health informatics, clinical decision-making, and computational medicine.

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Dr. Aristotelis Tsirigos on Pitt HexAI

Health and Explainable AI Podcast

33 minutes 41 seconds

1 year ago

Dr. Aristotelis Tsirigos on Pitt HexAI

Jordan Gass-Poore’, Pitt HexAI host, delves into the cutting-edge world of bioinformatics and cancer research with Dr. Aristotelis Tsirigos, a Professor of Medicine and Pathology and the Co-Director of Precision Medicine at NYU Grossman School of Medicine. Dr. Tsirigos shares his journey from computer science and electrical engineering to becoming a leading figure in pathology and bioinformatics.

In this episode, they explore the latest advancements in self-supervised deep learning and its transformative impact on cancer diagnosis and management. Dr. Tsirigos discusses his former work at IBM and his current research at NYU Langone Health's Perlmutter Cancer Center, including the innovative study "Mapping the landscape of histomorphological cancer phenotypes using self-supervised learning on unannotated pathology slides." This study, conducted in collaboration with the University of Glasgow, leverages AI to identify distinct cancer phenotypes, offering new insights into cancer subtypes and potential therapeutic strategies.

Tune in to learn about the intersection of AI, molecular information, and healthcare, and how these advancements are paving the way for more precise and personalized cancer treatments