About this module
Digital pathology, bioinformatics and artificial intelligence transform the practice of pathology worldwide. A.I. has been described as the fourth pathology revolution, clearly underlining the large expectations of this innovative technology.
This module will focus on the backgrounds of tissue section digitization, digital workflows and the opportunities to apply artificial intelligence techniques to aid the diagnostic process.
The module will be mostly pragmatic, focusing on real-world application more than theoretical background.
After finishing the module, the participant will be able to play an active role in the digitization of the microscopic workflow, introduce and validate A.I. solutions and participate in research projects that aim to develop and evaluate A.I. in pathology
Learning outcomes
- Describe steps needed to validate the use of whole-slide-imaging for primary diagnostics
- Name factors that need to be included in digital pathology quality management
- Explain the need for interoperability, and the use of standards
- Name three potential benefits of the use of digital pathology
- Name the three potential benefits of the use of AI in pathology diagnostics
- Name at least three examples of the use of AI in pathology diagnostics
- Describe different types of annotations, needed for development of AI, and explain in which situations these are used
- Explain in broad terms how AI models are trained, also describe the difference between fully, weakly and unsupervised learning
- Explain what is meant by ‘AI is a black box’
- Explain ethical challenges associated with AI in pathology
- Explain in broad terms the impact of IVDR on the use of AI in pathology
- Explain advantages and disadvantages of ‘working in the cloud’
- Explain challenges with the digital and computational pathology business case
Module coordinator
- Dr. Jeroen van der Laak
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Jeroen van der Laak is professor of computational Pathology at the department of Pathology of the Radboud University Medical Center in Nijmegen, The Netherlands and guest professor at the Center for Medical Image Science and Visualization (CMIV) in Linköping, Sweden.
His research focuses on the use of artificial intelligence for analysis of digitized histopathological images.
His research group was among the first to show the large potential of so-called deep learning algorithms for analysis of whole slide images. Further research focused on improvements in deep learning strategies to increase robustness and accuracy, as well as on application of deep learning for various tasks in histopathology.
In 2016 and 2017, he coordinated the CAMELYON grand challenges.
Dr van der Laak co-authored over 150 peer-reviewed publications and is member of the board of directors of the Digital Pathology Association. He is organizer of sessions at the European Congress of Pathology, MICCAI and Pathology Visions. Dr van der Laak is leading the ‘AI in Pathology’ taskforce of the European Society of Pathology and is overall coordinator of the IMI/EU funded Bigpicture project. Dr van der Laak is USCAP Nathan Kaufman laureate. In 2021, he founded the Radboudumc spinoff Aiosyn, for which he is CSO.