A team of researchers has built an artificial intelligence (AI) device to predict life expectancy in heart failure patients. The Machine Learning algorithm which is based on de-identified electronic health records data of around 5,732 ambulatory or hospitalized patients with heart failure at UC San Diego Health in the US. “We wanted to develop a tool that predicted life expectancy in heart failure patients, there are apps where algorithms are finding out all kinds of things, like products you want to purchase,” said Avi Yagil, Professor, University of California. “We needed a similar tool to make medical decisions. Predicting mortality is important in patients with heart failure. Current strategies for predicting risk, however, are only modestly successful and can be subjective,” Yagil elaborated.
From this model, a risk score was calculated that indicated a high or low risk of death by identifying eight readily accessible variables collected for the majority of patients with heart failure: Creatinine, Diastolic blood pressure, White blood cell count, blood urea nitrogen, Albumin, and Red blood cell distribution and Platelets. Yagil said, “the newly developed model was able to accurately predict life expectancy 88 percent of the time and performed substantially better than other popular published models. This tool gives us insight, for example, on the probability that a given patient will die from heart failure in the next three months or a year,” said researcher Eric Adler. “This is incredibly valuable. It allows us to make informed decisions based on a proven methodology and not have to look into a crystal ball,” he added.
The tool was further tested using de-identified patient information from the University of California, San Francisco, and a database derived from around 12 European medical centers. “It was successful in those cohorts as well,” said Yagil. “Being able to repurpose our findings in independent populations is of utmost importance, thus validating our methodology and its results,” Yagil added. Researchers said the partnership between cardiologists and physicists was significant in developing a reliable device, and wide experience and knowledge from both sides are likely to prove synergetic.