Why the study?
The ECG has gained new importance through digital recording, frequent use, and artificial intelligence processing capable of extracting novel clinical information.
Can artificial intelligence extract novel diagnostic and prognostic information from digital ECGs?
Can artificial intelligence extract novel diagnostic and prognostic information from digital ECGs?
AI analysis of digital ECGs significantly expands the diagnostic and prognostic capabilities of a traditional, low-cost, and widely available tool.
AI-augmented ECG analysis may yield novel biomarkers; leaves open prospective validation before clinical adoption.
The electrocardiogram (ECG), considered by some diagnosticians of cardiovascular diseases to be a slightly anachronistic tool, has acquired a completely new face and importance thanks to its three modern features: the digital form of recording, its very frequent use, and the possibility of processing thousands of records by artificial intelligence (AI). In this review of the literature on this subject from the first 3 months of 2023, the use of many types of software for extracting new information from the ECG is described. These include, among others, natural language processing, backpropagation neural network and convolutional neural network. AI tools of this type allow physicians to achieve high accuracy not only in ECG-based predictions of the patient's age or sex but also of the abnormal structure of heart valves, abnormal electrical activity of the atria, distorted immune response after transplantation, good response to resynchronization therapy and an increased risk of sudden cardiac death. The attractiveness of the presented results lies in the simplicity of the examination by the staff, relatively low costs and even the possibility of performing the examination remotely. The twelve studies presented here are just a fraction of the novelties that the current year will bring.
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Tomasz Rechciński (2023) studied this question.
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