Artificial intelligence (AI) could soon help doctors identify patients at high risk for heart conditions, thanks to research from the University of Leeds.
The team has trained an AI system called Optimise, which analyzed the health records of more than two million people.
The AI uncovered many cases of undiagnosed conditions and instances where patients weren’t receiving necessary medications to reduce their risk of heart failure and related complications.
Of the two million records reviewed, the AI flagged more than 400,000 people as high risk for heart failure, stroke, and diabetes. This group comprised 74% of patients who died from heart-related conditions.
Dr. Ramesh Nadarajah, a health data research fellow at the University of Leeds, emphasized the importance of early intervention. “Preventing conditions from worsening is often cheaper than treating them,” he said.
A pilot program with Optimise involved 82 high-risk patients. It revealed that one in five had undiagnosed moderate to high-risk chronic kidney disease.
Additionally, more than half of those with high blood pressure were prescribed new medications to manage their heart risk better.
Dr. Nadarajah highlighted the system’s ability to leverage existing data to provide new insights. He believes this approach could allow healthcare professionals to offer timely care, potentially easing pressures on the NHS.
The study suggests that AI-driven insights could be crucial in the early treatment of high-risk patients, ultimately saving lives and resources.
