Speaker: Vladimir Despotovic (Department of Medical Informatics, Luxembourg Institute of Health, Luxembourg)
Title: AI-driven digital pathology: a step towards precision medicine.
Time: Wednesday, 2024.06.12, 10:00 a.m. (CET)
Place: fully virtual (contact Jakub Lengiewicz or Elisa GÓMEZ DE LOPE to register)
Format: 30 min. presentation + 30 min. discussion
Abstract: The presentation will focus on state-of-the-art computer vision technologies and algorithms for analyzing high resolution Whole Slide Images in digital and computational pathology, and its application to automatic clinical diagnosis. Special attention will be paid to self-supervised and transfer learning strategies to leverage domain knowledge in addressing the challenges posed by limited data availability. We will further discuss translational considerations, emphasizing how these technologies can lead to more personalized diagnostics and treatment approaches.
Additional material:
V. Despotovic, S.-Y. Kim, A.-C. Hau, A. Kakoichankava, G. Klamminger, F. Borgmann, K.B.M. Frauenknecht, M. Mittelbronn, P.V. Nazarov, Glioma subtype classification from histopathological images using in-domain and out-of-domain transfer learning: An experimental study, Heliyon, 2024
Presentation available here: www.jlengineer...
The aim of the Machine Learning Seminar series is to host presentations on fundamental and methodological advances in data science and machine learning, as well as to discuss application areas presented by domain specialists. The uniqueness of the seminar series lies in its attempt to extract common denominators between domain areas and to challenge existing methodologies. Therefore, the focus is on theory and applications to a wide range of domains, including Computational Physics and Engineering, Computational Biology and Life Sciences, and Computational Behavioural and Social Sciences. The seminar aims to bring together young and experienced researchers from various disciplines to exchange ideas on Machine Learning techniques. It is currently affiliated with the University of Luxembourg and is run under the auspices of the DTU DRIVEN PRIDE project, funded by the FNR, and the widening participation DRIVEN project, funded by H2020. The seminar also welcomes talks by researchers from a wider collaborative network, including but not limited to early-stage researchers in RAINBOW ITN, as well as current and incoming individual Marie Skłodowska-Curie fellows.
The usual format is as follows: a short presentation (20-30 minutes) followed by a longer discussion (30-40 minutes). The usual time is Wednesdays at 10:00 a.m. (CET). If you are interested in joining, please contact Jakub Lengiewicz. See www.jlengineer.....
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