Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. From Wikipedia
Its Monte Carlo dropout–based confidence scoring enables a reliable AI–human collaboration for scalable MSI testing.