2nd Sorbonne-Heidelberg workshop on AI in medicine: machine learning for multi-modal data
Saved in:
| Other Authors: | , |
|---|---|
| Format: | Conference Paper |
| Language: | English |
| Published: |
Heidelberg
Universitätsbibliothek Heidelberg
28 Aug. 2025
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| Series: | Joint DFH/UFA workshop on AI in Medicine
2 |
| DOI: | 10.11588/heidok.00036956 |
| Online Access: | Resolving-System, kostenfrei: https://nbn-resolving.de/urn:nbn:de:bsz:16-heidok-369566 Resolving-System, kostenfrei: https://doi.org/10.11588/heidok.00036956 Verlag, kostenfrei, Volltext: http://www.ub.uni-heidelberg.de/archiv/36956 
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| Author Notes: | Jürgen Hesser, Xavier Fresquet (eds.) |
MARC
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| 500 | |a Machine Learning is transforming science, especially the way we do research in medicine. It can analyze non-linear dependencies of structured clinical data, and it is starting to support in the huge amount of existing text and other unstructured information to extract useful information using recent techniques based on large language models. There is also an increasing amount of specific omics data for each patient, which makes it hard to manually inspect all the details. This is where multimodal data analysis comes in, which is the focus of this year's AI in Medicine workshop. Researchers from Sorbonne and Heidelberg will give keynote speeches to provide insight into their research field, which will fuel discussions. It brings together junior and senior researchers from Sorbonne University, Heidelberg University, and their partner universities in 4EU+. Scientific exchange takes center stage through participants' presentations & posters, keynotes by invited speakers, and discussions. Key techniques are trained during hands-on sessions, and social events invite you to network while experiencing the unique setting of the oldest German university and the environment of a vibrant student city | ||
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