230万枚のスライドで学習したPRISM2、ピクセルではなく診断を生成
PaigeとMicrosoftは、230万枚のスライドと臨床レポートで学習し診断テキストを生成する病理モデルPRISM2を公開した。これにより病理学は画像分類から解釈可能な臨床対話へと移行する。
paige and microsoft introduced prism2, a perceiver-based encoder trained jointly on tissue tiles and pathology reports to interpret whole-slide images and answer diagnostic questions. the model aggregates thousands of tile embeddings per slide from a dataset of 2.3 million slides to generate text-based conclusions. this moves beyond standard image classification by integrating clinical context into the diagnostic loop. it signals a maturation of medical ai from simple detection tools to systems capable of complex reasoning and communication.