Clinical significance, challenges and limitations in using artificial intelligence for electrocardiography-based diagnosis

Clinical significance, challenges and limitations in using artificial intelligence for electrocardiography-based diagnosis

Abstract Cardiovascular diseases are one of the leading global causes of mortality. Currently, clinicians rely on their own analyses or automated analyses of the electrocardiogram (ECG) to obtain a diagnosis. However, both approaches can only include a finite number of predictors and are unable to e...

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Bibliographic Details
Main Authors: Cheuk To Chung, Sharen Lee, Emma King, Tong Liu, Antonis A. Armoundas, George Bazoukis, Gary Tse
Format: Article
Language:English
Published: BMC 2022-10-01
Series:International Journal of Arrhythmia
Subjects:
Electrocardiography
Artificial intelligence
Machine learning
Deep learning
Cardiovascular diseases
Online Access:https://doi.org/10.1186/s42444-022-00075-x

Internet

https://doi.org/10.1186/s42444-022-00075-x

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