Heart attacks could soon be diagnosed with better speed and accuracy than ever before thanks to a new AI tool. Researchers have developed an algorithm which they say could reduce pressure on A&E and reassure patients suffering from chest pain. A new study suggests that compared to current testing methods, their algorithm was able to rule out a heart attack in more than double the number of patients with an accuracy of 99.6 per cent. The team, from the University of Edinburgh, said this ability to quickly rule out a heart attack could greatly reduce hospital admissions and rapidly identify patients that are safe to go home. The current gold standard for diagnosing a heart attack involves measuring levels of the protein troponin in the blood.

An algorithm developed using artificial intelligence could help doctors to diagnose heart attacks in women more accurately and quicker than ever before, according to research we fund and being presented at the European Society of Cardiology Congress in Barcelona. Previous BHF-funded research has shown that women in the UK who have a heart attack receive poorer care than men at every stage. Women were 50 per cent more likely to receive a wrong initial diagnosis, highlighting the need for innovations to help close the heart attack gender gap. Measuring the protein troponin in the blood is the current gold standard for diagnosing a heart attack. However, the levels of troponin released by the heart varies between men and women, with age and other health conditions.

If you dial the emergency services in Denmark, soon you won't just get a human operator, but an artificially intelligent assistant will be listening in too. Developed by start-up Corti, the system kicks into action when some dials 112 in Copenhagen, then it starts listening for signs of a possible cardiac arrest. To do this, it first uses speech recognition software to transcribe what's being said before analysing the text. Once it is confident of a diagnosis, it flashes an alert on the screen for the operator to see. Identifying cardiac arrest over the phone is one of the trickiest tasks for an operator.