AI can predict heart attacks more accurately than doctors

The American College of Cardiology/American Heart Association (ACC/AHA) has developed a series of guidelines for estimating a patient's cardiovascular risk which is based on eight factors including age, cholesterol level and blood pressure. That's pretty accurate but Stephen Weng and his team set about to make it better. They built four computer learning algorithms, then fed them data from 378,256 patients in the United Kingdom. The systems first used around 295,000 records to generate their internal predictive models. Then they used the remaining records to test and refine them.