Dr. Faisal Mahmood is an Assistant Professor of Pathology at Harvard Medical School and Computational Pathology at Brigham and Women’s Hospital. Dr. Mahmood recently published an exciting new paper this year where he and his team built a deep learning model to accurately identify tumors of unknown origin on pathological slides (Lu et al., Nature 2021)

Pathology is one of the central pillars of medicine and here we really dive deep into how machine learning is pushing the boundaries of the field and our abilities to diagnose and recognize tumors. Enjoy!

Twitter: @TheMaMLPodcast

Interviewer: David JH Wu (@davidjhwu)

Producer: Aaron Schumacher (@a_schu95)

Cover Art: Saurin Kantesaria

1:20 Background in computational pathology

5:30 Interest in Pathology

10:20 Modern algorithms detecting biomarkers to better educate physicians

12:05 Using AI to identify tumors of unknown origin

17:10 Building the TOAD AI Model

21:50 Assessing the validity of the Toad Model

23:30 Determining inputs for the TOAD Model

26:30 Diversity with the TOAD Algorithm

27:40 Next steps for the project

33:15 Using AI to augment physicians' abilities

35:06 Advice for physicians interest in AI

37:00 Dream Research Project

38:40 Will AI make medical discoveries in the future?

40:38 Advice you would give to yourself in your 20's

41:55 Obtaining a Ph.D. in Japan

44:00 Closing thoughts

Paper: Lu et. al, “AI-based pathology predicts origins for cancers of unknown primary.” Nature, 2021