generate slides from the attachment l that explains architecture of the model training setup results - less than 4 slides - focus on BRAF prediction related content - left paste relevant figure and bullet point explanation on the right. succinct

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This research focuses on predicting BRAF status from H&E whole-slide images (WSIs) through a clinically grounded benchmark. It aims to validate pathology foundation models against BRAF labels, emphasizing the importance of clinically relevant validation beyond pretraining scales. The architecture utilizes tiled H&E WSIs as input, employing a frozen self-supervised learning (SSL) encoder for slide aggregation. The training process involves transforming tile embeddings into attention pooling,...