Washington DC: A study claimed that machine learning, modern bedrock of artificial intelligence, could predict death or heart attack with more than 90 per cent accuracy. The study was presented at The International Conference on Nuclear Cardiology and Cardiac CT (ICNC) 2019. Machine learning is used every day. Google's search engine, face recognition on smartphones, self-driving cars, Netflix and Spotify recommendation systems -- all use machine learning algorithms to adapt to the individual user. By repeatedly analysing 85 variables in 950 patients with known six-year outcomes, an algorithm'learned' how imaging data interacts.

Machine learning, a branch of artificial intelligence, has become more accurate than human medical professionals in predicting incidence of heart attack or death in patients at risk of coronary artery disease. Machine learning, a branch of artificial intelligence, was more accurate than human medical professionals in predicting myocardial infarction (MI) or death among patients suspected of having coronary artery disease (CAD), according to an abstract presented at the 2019 International Conference on Nuclear Cardiology and Cardiac CT, held May 12-14 in Lisbon, Portugal. Physicians routinely make treatment decisions using risk scores, which are based on few variables and are typically only moderately accurate for individual patients. Machine learning can use repetition and adjustment to exploit large quantities of data and identify complex patterns that may go unnoticed by humans. "Humans have a very hard time thinking further than three dimensions (a cube) or four dimensions (a cube through time)," said the study's lead researcher, Luis Eduardo Juarez-Orozco, MD, PhD, in a statement.

As scientists continue to toil away at creating machine learning algorithms that will one day enslave humanity save us all, artificial intelligence researchers have discovered that computers are outpacing human doctors in a number of important areas. We've already seen the ability of AI to spot things like cancer, and a new study reveals that a digital brain may also be better at predicting overall mortality and specific conditions such as heart attack with greater accuracy than a trained individual. The research, which was presented at the International Conference on Nuclear Cardiology and Cardiac CT, suggests that we may be fast approaching a day when artificial intelligence works hand-in-hand with medical professionals to anticipate life-threatening problems before they occur. The researchers, led by Dr. Luis Eduardo Juarez-Orozco of the Turku PET Centre in Finland, trained a machine learning algorithm on a data set of nearly 1,000 patients. The data, which spanned six years for each patient, included dozens of variables that the computer had to digest in order to draw correlations between instances of death and heart attack with data on various heart and blood flow readings.

Algorithms similar to those employed by Netflix and Spotify to customise services are now better than human doctors at spotting who will die or have a heart attack. Machine learning was used to train LogitBoost, which its developers say can predict death or heart attacks with 90 per cent accuracy. It was programmed to use 85 variables to calculate the risk to the health of the 950 patients that it was fed scans and data from. Patients complaining of chest pain were subjected to a host of scans and tests before being treated by traditional methods. Their data was later used to train the algorithm.