A machine-learning technology has surpassed human capabilities when it comes to predicting the chances of death or heart attacks, according to research presented today at the International Conference on Nuclear Cardiology and Cardiac in Lisbon, Portugal.
In testing, the algorithm, known as LogitBoost, analyzed 85 different variables from 950 patients—for which the researchers had followed for six years—identifying which of the participants had died or suffered heart attacks with an accuracy of more than 90 percent.
Machine learning (ML) is a form of artificial intelligence in which algorithms become better and better at predicting a given outcome without being explicitly programmed—usually through the intake of increasing amounts of data.
“These advances are far beyond what has been done in medicine, where we need to be cautious about how we evaluate risk and outcomes,” Luis Eduardo Juarez-Orozco, an author of the research from the Turku PET Centre, Finland, said in a statement. “We have the data but we are not using it to its full potential yet.”
For more see: Newsweek
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