Gender gap in heart attack diagnosis closed by AI

Heart attacks can be more accurately diagnosed regardless of pre-existing health conditions, age and sex with the help of AI-based software.
An algorithm developed using AI can help doctors diagnose heart attacks in women quicker and more accurately than ever before, as revealed by British Heart Foundation-funded research.
University of Edinburgh researchers have created an AI-grounded tool to help doctors make more precise heart attack diagnoses.
The device was performed dependably throughout the study, presented in Barcelona at the European Society of Cardiology Congress.
The researchers used data from just over ten thousand hospital patients, forty-eight per cent of which were women and then, an additional three thousand more people, thirty-one per cent of which were women, outside of the UK were used to authenticate it.
The CoDE-ACS programme utilises AI to combine routinely gathered patient data, such as medical history and observations, with the troponin blood test results when they arrive at the hospital.
The team concluded that CoDE-ACS had a ninety-nine per cent accuracy rate in ruling out a heart attack, signifying they may return home without risk. It also correctly identified patients whose final diagnosis was a heart attack and who would require additional testing with an approximate eighty per cent accuracy.
James Leiper, BHF associate medical director, has stated, “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.”