PRISM2基於230萬張切片訓練，生成診斷報告而非像素分類
paige和微軟發布了prism2，這是一個在230萬張切片和臨床報告上訓練的病理模型，用於生成診斷文本。它將病理學從圖像分類轉變為可解釋的臨床對話。
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.