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Powerful Medical
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28. March 2025
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3 min to read
  • Study

Artificial Intelligence Detection of Occlusive Myocardial Infarction from Electrocardiograms Interpreted as “Normal” by Conventional Algorithms

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Overview

Conventional ECG algorithms, humanly programmed to detect abnormalities based on fiducial points, frequently miss critical patterns of STEMI. AI-driven deep neural network models like PMcardio AI ECG offer significant potential in identifying these dangerous false negatives, reducing the risk of false reassurance, and enhancing clinical decision-making.

Published In: Journal of Personalized Medicine
Presented Date: March 28, 2025

Background

Some authors advocate that ECGs with conventional computer algorithm (CCA) interpretations of “normal” need not be immediately reviewed. However, such ECGs may actually manifest findings of acute coronary occlusion myocardial infarction (OMI). We sought to determine if such cases can be detected by artificial intelligence (AI).

Methods

We studied a retrospective series (2014–2024) of cases with ≥1 pre-angiography ECGs with a proven OMI outcome with a CCA ECG interpretation of “normal”. The OMI outcome was defined as (1) the diagnosis of acute type I MI, (2) an angiographic culprit with intervention, and (3) one of the following, (a) TIMI-0-2 flow, or (b) TIMI-3 or unknown flow, with high peak troponin or new wall abnormality. Each ECG as retrospectively interpreted by the PMcardio OMI AI ECG model. The primary analysis was the performance of AI in diagnosing “OMI” among these CCA “normal” ECGs.

Results

Forty-two patients with OMI met the inclusion criteria. The first ECG was interpreted as “normal” by the CCA in 88% of cases; AI interpreted 81% as OMI and 86% as abnormal. Of the 78 total ECGs interpreted by the CCA, 73% were diagnosed as “normal”. Of this 73%, AI identified 81% as abnormal and 72% as OMI.

Conclusion

The Conventional Computer Algorithm may interpret an ECG manifesting OMI as “normal”. AI not only recognized these as abnormal, but in 81% of patients, correctly recognized OMI on the first ECG and recognized 72% of all the CCA “normal” ECGs as OMI. It was rare for AI to diagnose a normal ECG for any OMI patient.


Authors: Shifa R. Karim, Hans C. Helseth, Peter O. Baker, Gabriel A. Keller, H. Pendell Meyers, Robert Herman, and Stephen W. Smith

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Powerful Medical leads one of the most important shifts in modern medicine by augmenting human-made clinical decisions with artificial intelligence. Our primary focus is on cardiovascular diseases, the world’s leading cause of death.

About PMcardio

PMcardio is the market leader in AI-powered diagnostics, addressing the world’s leading cause of death – cardiovascular diseases. The innovative clinical assistant empowers healthcare professionals to detect up to 40 cardiovascular diseases. In the form of a smartphone application, the certified Class IIb medical device interprets any 12-lead ECG image in under 5 seconds to provide accurate diagnoses and individualized treatment recommendations tailored to each patient.

About Powerful Medical

Established in 2017, Powerful Medical has embarked on a mission to revolutionize the diagnosis and treatment of cardiovascular diseases. We are a medical company backed by 28 world-class cardiologists and led by our expert Scientific Board with decades of experience in daily patient care, clinical research, and medical devices. The results of our research are implemented, developed, certified, and brought to market by our 50+ strong interdisciplinary team of physicians, data scientists, AI experts, software engineers, regulatory specialists, and commercial teams.

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Relevant Publications

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  • Study
  • Journal of Personalized Medicine
  • March 28, 2025

Artificial Intelligence Detection of Occlusive Myocardial Infarction from Electrocardiograms Interpreted as “Normal” by Conventional Algorithms

Conventional ECG algorithms, humanly programmed to detect abnormalities based on fiducial points, frequently miss critical patterns of STEMI. AI-driven deep neural network models like PMcardio AI ECG offer significant potential in identifying these dangerous false negatives, reducing the risk of false reassurance, and enhancing clinical decision-making.
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ECG Patterns of Occlusion Myocardial Infarction: a Narrative Review

This comprehensive review highlights the limitations of the traditional STEMI/NSTEMI classification for heart attacks and advocates for a more precise approach to diagnosis and patient triage. Instead of relying solely on standard ECG criteria, this method focuses on ECG patterns that more accurately reflect the severity of underlying coronary vessel disease. By identifying high-risk ECG changes beyond current STEMI guidelines, clinicians can detect heart attacks earlier, initiate treatment faster, and ultimately improve patient outcomes.
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PMcardio is CE-marked as class IIb medical device under EU MDR and only certified for marketing in the European Union and the United Kingdom. PMcardio technology has not yet been cleared by the US Food and Drug Administration (FDA) for marketing in the USA. Not all modules of the PMcardio platform may be available in your region.

Prior to use, reference the Instructions for Use, for more detailed information on Indications, Contraindications, Warnings, Precautions and Adverse Events.

PMcardio is CE-marked as class IIb medical device under EU MDR and only certified for marketing in the European Union and the United Kingdom. PMcardio technology has not yet been cleared by the US Food and Drug Administration (FDA) for marketing in the USA. Not all modules of the PMcardio platform may be available in your region. Prior to use, reference the Instructions for Use, for more detailed information on Indications, Contraindications, Warnings, Precautions and Adverse Events.

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