Fig. 1: Workflow scheme.

a H&E-stained tissue slides were digitized by a scanner to obtain whole-slide images. b A large set of quantitative image features were extracted, characterizing nucleus size, staining, shape, and density. c The Mann–Whitney U test was used to compare image features between TFE3-RCC and ccRCC, and machine learning models were developed based on the image features to automatically classify the two cancer subtypes. On the box plots in c, the central mark indicates the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles (q₁ and q₃), respectively. The upper whisker extends from q₃ to q₃ + 1.5 × (q₃ − q₁), and the lower whisker extends from q₁ to q₁ − 1.5 × (q₃ − q₁), while data beyond the end of the whiskers are outlying points that are plotted individually.