Leeds researchers develop AI technology to detect heart failure earlier

Artificial intelligence (AI) could be used to identify patients at risk of heart failure, meaning they could be treated earlier, Leeds researchers said.

An algorithm, known as Find-HF, has been ‘trained’ by researchers at the University of Leeds to detect early symptoms of the condition using patient records.

According to the British Heart Foundation (BHF), there are currently more than one million people in the UK with heart failure.

Professor Chris Gale, from Leeds Teaching Hospitals NHS Trust and the University of Leeds, said the technology would open a “crucial window of opportunity” for patients.

For the study, which was funded by the BHF, researchers used the patient records of 565,284 UK adults to train the AI ​​algorithm,

It was then further tested on a database of 106,026 records from the National Taiwan University Hospital.

The AI ​​was able to accurately predict patients at highest risk of developing heart failure and those likely to be hospitalized with the condition within five years, the researchers said.

Consultant cardiologist Prof Gale said: “This is an extremely powerful and unique national resource and it is time to use this data to benefit patients.

“Find-HF could bring diagnoses two years ahead.”

The researchers suggested the platform could be used by family doctors as an early warning system, allowing them to test and diagnose patients earlier.

Dr Ramesh Nadarajah, UK health researcher at the University of Leeds, said: “Many people are diagnosed with heart failure at too late a stage when disease-modifying treatments are potentially less effective, particularly women and the elderly.

“We use machine learning tools with routinely collected data to identify people with heart failure earlier so they can receive the right treatment and prevent hospital admissions and death and improve quality of life.”