Digital Pathology Bioinformatics & AI EMMP SYLLABUS TEMPLATE

syllabus

Module Overview

Learning Outcomes

Module 8 Digital Pathology Bioinformatics & AI

Schedule

Evaluation method

Year 2

Your Module Coordinators

Your Module Teachers

Module Overview

Digital pathology, bioinformatics and artificial intelligence transform (A.I.) 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 pathologyThis module highlights the transformative impact of digital pathology, bioinformatics, and A.I. on the practice of pathology worldwide and aims to improve the competency and knowledge of pathologists using these technologies, while also providing guidance on their validation and verification for standardised clinical use.

Campus

Workload

100% Online: This learning space will be open 1 month before your on-campus classes. You will have access to this course for the whole of your time as an MSc EMMP student.

3ECTS = approximately 75 hours total study load (online, in-person, and self-study/research)

Learning Outcomes

By the end of this module, you should be able to...

• explain basic concepts about digital and computational pathology
• critically appraise a commercial digital pathology solution
• support the development of computational pathology algorithms, mostly focussing on problem definition and data collection/annotation
• reflect on ethical issues with the use of DP and CP

Schedule

Evaluation

Evaluation

You will have 3 evaluations in this module. The final grade for module 8 will be average of the 3 taking into consideration the weighting of each evaluation

Evaluations

Assessment Topic 5: Preparation: each student will do the experiment (Score 10 images, each) for TCF and Ki-67 – as per the original slide seminar survey (Frei, Mod Pathol, 2023); try the PathChat demo. Important date: 28th November - Deadline submission of homework for Topic 5 experiment

Assessment Topic 2: Evaluation of topic 2 will consist of a practical quiz on a selected area of a whole slide image or a full whole slide image. Questions related with the production of whole slide images and practical use of computational tools will be addressed. The practical quiz lasts for 10 minutes maximum and happens during an individual online session with one of the teachers of this topic. Important dates: 3rd December at 4-6pm CET - Evaluation of the first 13 students, per alphabetic order of the first name (given name) 4th December at 4-6pm CET - Evaluation of the last 13 students, per alphabetic order of the first name (given name)

Assessment Topic 6: Essay Assignment: Ethical Considerations in Digital Pathology. For this assignment, students are required to write an essay focusing on ethical issues in digital pathology. Two case scenarios and a set of discussion points will be provided. Students need to pick ONE of these scenarios and answer the questions in a short (1 A4 - 500 words) essay. Further instructions can be found in the Moodle documentation on Topic 6. Important date: 15th December - Deadline for submission essay

GRADING

ASSIGNMENTS

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Your Module Coordinator

Jeroen van der Laak is professor in Computational Pathology and principle investigator at the Department of Pathology of 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 group investigates the use of deep learning-based whole-slide image analysis for different applications; improvement of routine pathology diagnostics, objective quantification of immunohistochemical markers, and study of novel imaging biomarkers for prognostics.

Jeroen van der Laak

Info

Your Module Teachers

Catarina Eloy is a Portuguese interventional pathologist, researcher, and teacher devoted to the diagnosis and study of thyroid cancer.

Frédérique Meeuwsen is a visiting pathology resident from Erasmus MC in Rotterdam.

Inti Zlobec elected Digital Pathology Professor

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She graduated as pathologist in 2011, completed her PhD thesis on papillary thyroid carcinoma in 2012 by the Medical Faculty of Porto University, is Affiliated Professor of the Medical Faculty of Porto University since 2015 and published more than 100 manuscripts in indexed scientific journals. She is the Head of the fully digital Pathology Laboratory of Ipatimup, Porto, since 2013 and developed special interest in the modernization of the diagnostic processes, including digital and computational pathology. She is member of the European Society of Pathology (ESP) since 2010, chair of the Educational Subcommittee since 2023, member of the Council since 2023, member of the Advisory Board since 2022, member of the Editorial Board of Virchows Archiv since 2022, coordinator of the ESP - Training Centre for Digital Pathology at IPATIMUP since 2022 and was co-chair of the Endocrine working group from 2018 to 2022. She is Vice-President of the Portuguese Society of Pathology, member of the Endocrine Pathology Society since 2023 and was President of the European Society of Digital and Integrative Pathology (2020-2022). Since 2024, she is member of the Computational pathology subcommittee of IARC/WHO.