135P Comprehensive benchmarking of vision-language models for brain tumor molecular classification
Qin Zeng(Else Kröner-Fresenius-Stiftung), Jakob Nikolas Kather(Heidelberg University), S. Sainath(Else Kröner-Fresenius-Stiftung), L Bejan(The London College), Zunamys I. Carrero(Helmholtz-Zentrum Dresden-Rossendorf), Juan Pablo Ricapito(Else Kröner-Fresenius-Stiftung), Thomas O Millner(Queen Mary University of London), Sebastian Brandner(Universitätsklinikum Erlangen), Katherine Hewitt(University Hospital Carl Gustav Carus)
Cited by 0
Related Papers
Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer
|Nature Medicine|2019|1.4k
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
|PLoS Medicine|2019|1k
The future landscape of large language models in medicine
|Communications Medicine|2023|937
Deep learning in cancer pathology: a new generation of clinical biomarkers
|British Journal of Cancer|2020|649
Pan-cancer image-based detection of clinically actionable genetic alterations
|Nature Cancer|2020|630