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Found 3 papers, 1 papers with code
Autonomous Artificial Intelligence Agents for Clinical Decision Making in Oncology
We believe, that our work can serve as a proof-of-concept for more advanced LLM-agents in the medical domain.
In-context learning enables multimodal large language models to classify cancer pathology images
Medical image classification requires labeled, task-specific datasets which are used to train deep learning networks de novo, or to fine-tune foundation models.
A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification
We question this belief in the context of weakly supervised whole slide image classification, motivated by the emergence of powerful feature extractors trained using self-supervised learning on diverse pathology datasets.
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