AI has learnt to predict heart attacks more accurately than doctors

Every year an estimated 20 million people die from heart disease, but now, hot on the heels of an artificial intelligence (AI) system that can predict death, a team of researchers from the University of Nottingham, the same university that's found a way to regrow teeth from stem cells, have developed a machine learning algorithm that can predict an individuals likelihood of having a heart attack, or a stroke, better than any doctor. Over the past few decades the American College of Cardiology and the American Heart Association (ACC-AHA) has developed a series of guidelines to help doctors evaluate a patient's cardiovascular risk, based on eight factors that include age, cholesterol level and blood pressure. You might think that's already good enough – but Stephen Weng and his team wanted to make it even better so they built four computer learning algorithms and fed them data from over 380,000 patients. Firstly, the new system used 295,000 records to build its internal predictive models, and then it used the remaining 85,000 records to test and refine them, and the result? After all, you don't want to be told you're likely to have a heart attack if you aren't – doctors aren't beasts you know… Translating all of that into normal language what this all means is that out of the 85,000 records it analysed the new model could have saved 355 lives, but interestingly the AI system identified a number of risk factors and predictors not covered in the existing guidelines, like severe mental illness and the consumption of oral corticosteroids.