Fig. 4

Correlation between semiquantitative scores and deep learning-derived measures for the amyloid-β model. Leptomeningeal vessels differentially affected by CAA are shown (a absent; b mild; c moderate; d severe) together with the related deep learning-derived prediction (a’–d’). Similarly, representative cortical vessels with different degrees of CAA accumulation are shown (f absent; g mild; h moderate; i severe) together with the related deep learning-derived prediction (f’-i’). Finally, degrees of Aβ-plaque severity are shown (k absent; l mild; m moderate; n severe) together with the deep learning-derived prediction of the same area (k’–n’) Box plots show the correlation between semiquantitative visual scores obtained in a total number of 65 whole slides for leptomeningeal CAA (e), cortical CAA (j), and Aβ-plaques (o) and the respective measure obtained using the deep learning-model. Interquartile range (top and bottom of the box), median (central band), outliers (data points beyond the whiskers), and individual data points are visualized. Key: green = cortical tissue; yellow = leptomeningeal tissue; red = CAA; blue = Aβ-plaques