AI mimics the way doctors think to make better medical diagnoses

A new way of training medical artificial intelligence (AI) systems has proven significantly more accurate at diagnosing illnesses than previous efforts. The AI system developed by researchers at University College London and Babylon Health, a medical service provider in the UK, relies on causation rather than correlation to pinpoint what could be wrong with people. It is more accurate than pre-existing AI systems and even outperformed real-life doctors in a small, controlled trial. Unlike traditional AI systems, which identify the most probable disease based on symptoms presented by a patient, the causal AI system more closely mimics the way a doctor diagnoses patients: by using counterfactual questions to narrow the range of possible conditions. A patient could present at a hospital with shortness of breath.