New York, Researchers have developed an artificial intelligence (AI) tool to predict life expectancy in heart failure patients.
The machine learning algorithm based on de-identified electronic health, records data of 5,822 hospitalised or ambulatory 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 at 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 added.
From this model, a risk score was derived that determined low and high risk of death by identifying eight readily available variables collected for the majority of patients with heart failure:Diastolic blood pressure, Creatinine, Blood urea nitrogen, White blood cell count, Platelets, Albumin and Red blood cell distribution.
https://cio.economictimes.indiatimes.com/news/enterprise-services-and-applications/ai-tool-to-predict-life-expectancy-in-heart-failure-patients/72056335
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