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- W4386880708 endingPage "102097" @default.
- W4386880708 startingPage "102097" @default.
- W4386880708 abstract "Artificial Intelligence (AI) is already widely used in different fields of medicine, making possible the integration of the paraclinical exams with the clinical findings in patients, for a more accurate and rapid diagnosis and treatment decision. The electrocardiogram remains one of the most important, fastest, cheapest, and noninvasive methods of diagnosis in cardiology, despite the rapid development and progression of the technology. Even if studied since a long time ago, it still has a lot of less understood features that, with a better understanding, can give more clues to a correct and prompt diagnosis in a short time. The use of AI in the interpretation of the ECG improved the accuracy and the time to diagnosis in different cardiovascular diseases, and more than this, explaining the decision to make AI diagnosis improved the human understanding of the different features of the ECG that might be considered for a more accurate diagnosis. The purpose of this article is to provide an overview of the most recent published articles about the use of AI in ECG interpretation." @default.
- W4386880708 created "2023-09-21" @default.
- W4386880708 creator A5019243077 @default.
- W4386880708 creator A5025175618 @default.
- W4386880708 date "2024-01-01" @default.
- W4386880708 modified "2023-10-18" @default.
- W4386880708 title "Electrocardiogram Interpretation Using Artificial Intelligence: Diagnosis of Cardiac and Extracardiac Pathologic Conditions. How Far Has Machine Learning Reached?" @default.
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- W4386880708 doi "https://doi.org/10.1016/j.cpcardiol.2023.102097" @default.
- W4386880708 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37739276" @default.
- W4386880708 hasPublicationYear "2024" @default.
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