Random forest results

Random forest crosstable and feature results based on digital pathology features. Classifications were conducted between disease (C9-ALS) and control "conditions" overall, divided by marker (CD68/FUS/GFAP/Iba1/TDP43), brain region (BA), matter type (GM/VM), or vascular adjacency (VA). Classifications for subregions are shown as "marker-region", "marker-region-matter" and "all variables". Crosstables show how many images the model correctly classified. <br>"Features" files show which features, when left out, reduced or improved the ability of the model to accurately classify images.<br>"Impairment", "duration" and "ALSFRS" files show the inability of the model to accurately classify between these condition types (as opposed to disease versus control). <br>