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AI Outperforms Doctors in Detecting Hidden Heart Attacks, Study Shows

A study presented at the ESC Acute CardioVascular Care congress found an AI algorithm for interpreting ECGs was significantly more accurate than standard clinical pathways in detecting a specific type of heart attack known as occlusive myocardial infarction, particularly in patients without the classic ST elevation on their ECG. The AI method correctly identified the condition in 84% of cases, compared to 42% for human ECG interpretation. The research suggests this tool could help clinicians provide faster, more accurate emergency treatment. The findings require further validation but highlight AI's potential as a valuable decision-support tool in acute cardiovascular care.

Key Points: AI Beats Standard Diagnosis for Certain Heart Attacks

  • AI detected occlusive MI in 84% of cases
  • Superior to human ECG interpretation (42%)
  • Study of 1,490 patients without ST elevation
  • High specificity (99%) and negative predictive value (98%)
3 min read

AI outperforms conventional diagnosis for certain types of heart attacks: Study

New study finds AI-based ECG interpretation is more accurate than conventional methods for detecting occlusive myocardial infarction without ST elevation.

AI outperforms conventional diagnosis for certain types of heart attacks: Study
"This simple, accessible AI-based approach demonstrated superior accuracy... - Doctor Federico Nani"

Sophia Antipolis, March 20

An artificial intelligence-based method for interpreting ECGs performed better than standard approaches in detecting occlusive myocardial infarction, according to a study presented at ESC Acute CardioVascular Care 2026, the annual congress of the Association for Acute CardioVascular Care, a branch of the European Society of Cardiology.

In patients with suspected acute coronary syndrome (ACS), a specific change on an ECG, called an ST elevation, is an indicator that the patient may have an occlusion in a coronary artery. This type of heart attack is known as an ST-elevation myocardial infarction (STEMI) and it requires immediate percutaneous coronary intervention to restore the heart's blood flow. In patients who do not have an ST elevation, the cause of the chest pain can be less certain and further tests are needed to confirm if the MI is due to an occlusion.

Presenter, Doctor Federico Nani from Central Hospital Bolzano, Italy, explained: "Many patients without an ST elevation have an occlusive MI, but it can be difficult for clinicians to quickly and accurately recognise this, leading to delays in providing emergency treatment. We investigated whether AI-based interpretation of the initial ECG could improve the accuracy of detecting occlusive MIs in the absence of an ST elevation to optimise patient management."

This single-centre prospective study included 1,490 patients who had symptoms suggestive of ACS but without an ST elevation on the initial ECG. The mean age was 63 years and 42 per cent were female. Clinicians interpreted the initial ECG, tested levels of the cardiac biomarker troponin, and performed coronary angiography, when required, to diagnose occlusive MI based on ESC Guidelines. In parallel, the initial ECG was interpreted by a smartphone-based CE-certified AI-ECG algorithm.

AI-based ECG interpretation ruled out occlusive MI in 1,382 patients and detected it in 108 patients (7per cent). The AI-based method correctly identified obstructive MI in 84per cent of cases. Sensitivity was 77per cent, specificity was 99 per cent, and the negative predictive value was 98 per cent. There were 27 false negatives (2per cent) and 17 false positives (1per cent).

According to the standard diagnostic pathway, occlusive MI was ruled out in 1,207 patients based on troponin levels, and 283 patients underwent coronary angiography to confirm or exclude the diagnosis. Overall, human ECG-interpretation correctly identified occlusive MI in 42per cent of cases.

Doctor Nani concluded: "This simple, accessible AI-based approach demonstrated superior accuracy in identifying and excluding occlusive MI compared with conventional diagnostic pathways in patients without an ST elevation. The results of our single-centre study require further validation, but these findings suggest that AI ECG interpretation is a valuable addition to existing decision-making tools to improve early recognition and timely, effective treatment."

The power of AI to support the management of cardiovascular disease will be further explored as the spotlight theme of this year's annual ESC Congress, taking place from 28-31 August 2026 in Munich, Germany.

- ANI

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Reader Comments

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Priyanka N
Very promising study, but we must be cautious. A 2% false negative rate means some patients could be sent home when they actually need urgent care. In our context, where patients often present late to hospitals, we cannot afford any missed diagnoses. AI should assist, not replace, the clinician's judgment.
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Arun Y
Fantastic! 84% accuracy vs 42% for human interpretation is a massive leap. Imagine this being used in primary health centres or even by ambulance paramedics in tier-2 and tier-3 cities. Early detection is key for heart attacks. Technology like this can truly bridge the urban-rural healthcare gap.
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Sarah B
As someone with a family history of heart disease, this gives me hope. My father had chest pains that were dismissed initially. A tool that gives doctors a second, highly accurate opinion could prevent such tragedies. The key will be integrating it seamlessly into hospital workflows.
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Karthik V
The study is on a smartphone-based app? That's the real news! If it's CE-certified and works on a phone, it could be deployed rapidly. However, the cost is a major factor. Will it be a subscription model that only corporate hospitals can afford, or will there be a scalable model for government hospitals?
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Meera T
Heartening to see such advancements. But we also need to focus on prevention. Alongside AI for diagnosis, we need more awareness about lifestyle diseases in India. Junk food, stress, and lack of exercise are creating a heart disease epidemic. Tech is a tool, not a substitute for healthy living.

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