Regulating the Black Box of Medical AI – Using data to make healthcare better

April 2016 One of the largest suppliers of electronic healthcare record systems to General Practitioners in the UK realise that an algorithm used to estimate patients' risk of heart disease or stroke has been coded incorrectly. As a result of this simple programming error, thousands of patients were given incorrect information about their risk, potentially receiving unnecessary drugs or missing out on preventative treatment. Feb 2017 Researchers from Stanford University publish a research letter in Nature describing the use of a deep convolutional neural network (a type of machine learning algorithm that takes inspiration from the layered structure of the part of the brain responsible for vision) to diagnose skin cancer. By training the algorithm on 130000 pictures of assorted spots, rashes, blemishes and skin lumps, the neural network was able to diagnose skin cancers with the same level of accuracy as qualified dermatologists. In principle, the system could be used to automatically diagnose likely skin cancers from a smartphone snap: skin selfie to diagnosis in seconds.