British Heart Foundation (BHF)-funded research has revealed that an algorithm developed using artificial intelligence can help doctors to diagnose heart attacks in women more accurately and quicker than ever before.

The researchers at the University of Edinburgh created an AI-based tool to aid doctors in making more accurate heart attack diagnoses.

BHF said that AI-based software can help clinicians diagnose heart attacks more accurately regardless of sex, age and pre-existing health conditions.

Presented at the European Society of Cardiology Congress in Barcelona, the device was performed consistently throughout the study.

Researchers used data from 10,038 (48% women) hospital patients with suspected heart attacks and then, 3,035 more people (31% women) outside of the UK were used to authenticate it.

The CoDE-ACS programme employs AI to combine the troponin blood test results with routinely gathered patient data (observations, ECG readings, and medical history) when they arrive at the hospital.

The team discovered that CoDE-ACS had a 99.5% accuracy rate in ruling out a heart attack, indicating they may return home without risk.

With an accuracy of 83.7%, it also correctly identified patients whose final diagnosis was a heart attack and who would benefit from staying in the hospital for additional testing.

BHF said that less than half of individuals indicated for additional testing using the existing methods had a heart attack diagnosis.

BHF associate medical director James Leiper said: “This is a huge step forward which promises to ensure everyone is on a level playing field when it comes to heart attack diagnosis and treatment.

“We know that women are more likely to receive a misdiagnosis, but by harnessing the power of AI, this team could provide one solution that helps to make that an issue of the past.”