
The author presents a Federated Attention Contrastive Learning (FACL) framework to improve model generalization in cancer diagnosis and Gleason grading tasks, addressing data heterogeneity and privacy concerns.


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Federated-Attention-Contrastive-Learning-Models-for-Prostate-Cancer-Diagnosis-and-Gleason-Grading


Federated Attention Contrastive Learning Models for Prostate Cancer Diagnosis and Gleason Grading


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FACL bietet ein robustes, genaues und kostengünstiges KI-Trainingsmodell für die Pathologie des Prostatakrebses, während effektive Datenschutzmaßnahmen aufrechterhalten werden.
