Fig. 2

Pipeline of preprocessing, model training, and evaluation. During preprocessing, the study images were converted to grayscale; the images were then transformed into features. The features were extracted using five different pretrained Vision Transformer (ViT) models. Subsequently, least absolute shrinkage and selection operator (LASSO) regression with additional variance filtering for feature selection were applied, resulting in a reduction to a final feature set of 72 predictors