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56: The beginnings of computational pathology w/ Jeroen van der Laak, Radboud UMC
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Treść dostarczona przez Aleksandra Zuraw, DVM, PhD, Aleksandra Zuraw, and DVM. Cała zawartość podcastów, w tym odcinki, grafika i opisy podcastów, jest przesyłana i udostępniana bezpośrednio przez Aleksandra Zuraw, DVM, PhD, Aleksandra Zuraw, and DVM lub jego partnera na platformie podcastów. Jeśli uważasz, że ktoś wykorzystuje Twoje dzieło chronione prawem autorskim bez Twojej zgody, możesz postępować zgodnie z procedurą opisaną tutaj https://pl.player.fm/legal.
Computational pathology – how did this field even start?
In today’s episode my guest is Jeroen van der Laak, computational pathology professor at Radboud University Medical Center, who was recently listed on "The Pathologist Power List" in the category “Strange New worlds”
Jeroen has been in the field of computational pathology for over 30 years and has seen it being created and evolve.
He witnessed how advancements in whole-slide imaging and deep learning have allowed for the practical application of AI in pathology.
Throughout the evolution of the field of computational pathology the focus has shifted from research-oriented work to direct collaboration with clinicians to test AI in diagnostic practice.
During his tenure Jeroen has seen what it takes to be successful in the field of computational and digital pathology.
To be a successful researcher in this field you need to understand the importance of high quality data and understand how the field of pathology works and what you see in the tissue you are analyzing.
This is a very collaborative field and a responsibility of an AI researcher is making AI accessible and breaking down technical aspects for pathologists.
Jeroen co-leads the Computational Pathology Group at Radboud with two other researchers – Francesco Ciompi and Geert Litjens. Their criteria for choosing successful candidates for a digital pathology group include good team spirit, collaboration, willingness to learn, and understanding of the field.
It is just a matter of (not too much) time when AI will become mainstream in pathology labs and will improve the accuracy and speed of patient diagnosis. Just like whole slide scanning is becoming part of the routine pathology workflow, so will AI based image analysis.
THIS EPISODES RESOURCES
- This episode on YouTube
- "Bridging the gap between pathology and computer science" - full event on YouTube
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