New framework renders AI more trustworthy for cancer subtyping

Article excerpt

Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks are largely unaware of the limits of their training data and can become overconfident when confronted with unfamiliar inputs. Suppose you train a neural network to distinguish among African mammals. If you then present it with an image of a South American jaguar, an animal it has never encountered, the model cannot say "unknown." Instead, it may confidently declare the jaguar to be a leopard.