New AI tech will detect the risks of heart failure at early stage

Researchers in Leeds have highlighted that artificial intelligence (AI) could help identify patients at risk of heart failure, enabling earlier intervention and treatment, the BBC reports.

The AI algorithm, named Find-HF, was developed by researchers at Leeds University to detect early signs of heart failure using patient records.

According to the British Heart Foundation (BHF), over one million people in the UK currently suffer from heart failure. Prof Chris Gale, from Leeds Teaching Hospitals NHS Trust and the University of Leeds, stated that this technology could provide a "crucial window of opportunity" for patient care.

The study, funded by the BHF, involved using patient records from 565,284 UK adults to train the AI. It was then tested on a separate database of 106,026 records from Taiwan National University Hospital. The AI successfully predicted which patients were at the highest risk of developing heart failure and those likely to be hospitalized within five years.

Quality of Life

Prof Gale, a consultant cardiologist, emphasized the importance of utilizing this "extremely powerful and unique national resource" to benefit patients, suggesting that Find-HF could advance diagnoses by up to two years.

Researchers propose that general practitioners could use this platform as an early warning system to test and diagnose patients sooner.

Dr. Ramesh Nadarajah, a health data research fellow at the University of Leeds, pointed out that many heart failure diagnoses are made too late for effective treatment, especially in women and older adults.

"We are using machine learning tools with routinely collected data to identify people with heart failure earlier, so that they can get the right treatment and prevent hospital admissions and death, and improve quality of life," he said.