Leeds researchers build AI algorithm to help early detection of heart failure

The researchers at Leeds University have built an algorithm that is trained to detect early symptoms of heart failure using the previous records of a patient.

The AI algorithm, Find-HF, was trained using the patient records of 565,284 UK adults. Further on, it was tested on a database of 106,026 records from Taiwan National University Hospital.

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

The algorithm will be used for the early detection of heart failure. According to the researchers at the UK-Based university, Artificial intelligence (AI) could be used to identify patients at risk of heart failure, which can help in early treatment of the condition.

The study was funded by the British Heart Foundation (BHF), which said there are currently one million people in the UK with heart failure.

Prof Chris Gale, Leeds Teaching Hospitals NHS Trust and the University of Leeds, termed the algorithm as “an extremely powerful and unique national resource.”

"Find-HF could potentially bring diagnoses forward by two years,” said prof Gale. Dr Ramesh Nadarajah, a health data research UK fellow at the University of Leeds also said the platform will prove to be a boon for lot of people, especially women and elderly. 

The researchers suggested that General Physicians could use the platform as an early warning system, enabling early diagnosis of patients and help them provide with right treatment.