In-context learning enables multimodal large language models to classify cancer pathology images

In-context learning enables multimodal large language models to classify cancer pathology images

Abstract Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models. However, this process is computationally and technically demanding. In language processing, in-context learning provides an altern...

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Podrobná bibliografie
Hlavní autoři: Dyke Ferber, Georg Wölflein, Isabella C. Wiest, Marta Ligero, Srividhya Sainath, Narmin Ghaffari Laleh, Omar S. M. El Nahhas, Gustav Müller-Franzes, Dirk Jäger, Daniel Truhn, Jakob Nikolas Kather
Médium: Článek
Jazyk:English
Vydáno: Nature Portfolio 2024-11-01
Edice:Nature Communications
On-line přístup:https://doi.org/10.1038/s41467-024-51465-9

Internet

https://doi.org/10.1038/s41467-024-51465-9

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