Is artificial intelligence really that smart?

Published:August 05, 2022DOI:
      Artificial intelligence (AI) and machine learning (ML) are the latest research buzzwords in everything from the medical and social sciences to consumer products. AI invokes excitement and apprehension from both its potential and its unintended consequences. For the electrophysiology community, AI is relatively familiar. Computer-generated electrocardiogram (ECG) interpretation is a rudimentary form of AI, and we are reminded of its limits every time we correct errors in these interpretations. Advanced 3-dimensional mapping systems use algorithms to map complex arrhythmias. Cardiac electrophysiologists have historically relied on their analytical reasoning to use indirect and incomplete data to identify and ablate cardiac arrhythmias with pinpoint precision. With advances in the computational processing of large data sets, researchers are exploring whether AI can match or exceed this analytical skill.
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        • Zhao W.
        • Zhu R.
        • Zhang J.
        • et al.
        Machine learning for distinguishing right from left premature ventricular contractions origin using surface electrocardiogram features.
        Heart Rhythm. 2022; 19: 1781-1789
        • Waxman H.L.
        • Josephson M.E.
        Ventricular activation during ventricular endocardial pacing: I. Electrocardiographic patterns related to the site of pacing.
        Am J Cardiol. 1982; 50: 1-10
        • Miller J.M.
        • Marchlinski F.E.
        • Buxton A.E.
        • Josephson M.E.
        Relationship between the 12-lead electrocardiogram during ventricular tachycardia and endocardial site of origin in patients with coronary artery disease.
        Circulation. 1988; 77: 759-766
        • Yokokawa M.
        • Liu T.Y.
        • Yoshida K.
        • et al.
        Automated analysis of the 12-lead electrocardiogram to identify the exit site of postinfarction ventricular tachycardia.
        Heart Rhythm. 2012; 9: 330-334
        • Sapp J.L.
        • Bar-Tal M.
        • Howes A.J.
        • et al.
        Real-time localization of ventricular tachycardia origin from the 12-lead electrocardiogram.
        JACC Clin Electrophysiol. 2017; 3: 687-699
        • Yang T.
        • Yu L.
        • Jin Q.
        • Wu L.
        • He B.
        Localization of origins of premature ventricular contraction by means of convolutional neural network from 12-lead ECG.
        IEEE Trans Biomed Eng. 2017; 65: 1662-1671

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