Computational pathology in precision oncology: evolution from task-specific models to foundation models. (IMAGE)
Caption
Traditional task-specific computational pathology models require a substantial labeled dataset for training to perform various tasks, while foundation models can be trained on large-scale, unlabeled datasets and fine-tuned with a small amount of labeled data to adapt to multiple downstream tasks. Foundation models are paving new frontiers in computational pathology and precision oncology, improving precision and accuracy, lowering health care costs, and improving patient treatment experiences.
Credit
Chinese Medical Journal Image source link: https://journals.lww.com/cmj/fulltext/9900/computational_pathology_in_precision_oncology_.1754.aspx
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