Foundation models in pathology

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초록

Foundation models prepare neural networks for applications in specific domains, such as speech applications or image analysis, through self-supervised pretraining. These models can be adapted for specific applications, such as histopathological diagnostics. While adaptation still requires supervised training, AI applications based on foundation models achieve significantly better prediction accuracy with fewer training data compared to conventional approaches. This article introduces the topic and provides an overview of foundation models in pathology.

키워드

Artificial intelligence; Computer-assisted image processing; Histopathology; Machine learning; Machine learning; Foundation models; Foundation models; Neural networks; Neural networks; Machine learning; Foundation models; Neural networks
제목
Foundation models in pathology
저자
Klauschen, Frederick; Dippel, Jonas; Mueller, Klaus-Robert
DOI
10.1007/s00292-025-01429-7
발행일
2025-05
유형
Review
저널명
Pathologie
권
46
호
3
페이지
152 ~ 155