The AI-based algorithms analyze pathological specimens of gliomas and predict outcomes based on genetic and molecular markers, including isocitrate dehydrogenase (IDH) mutation status, 1 p/19 co-deletion status, O-6-methylguanine-DNA methyltransferase (MGMT) methylation status, epidermal growth factor receptor splice variant III (EGFRvIII), Ki-67 marker expression, prediction of p53 status in gliomas, prediction of mutations in BRAF, and catenin β-1 in craniopharyngiomas [96,98,100,101,102,103]. The gene discussed is MKI67; the disease is glioma.