Electrocardiogram Abnormality Detection Using Machine Learning on Summary Data and Biometric Features

Electrocardiogram Abnormality Detection Using Machine Learning on Summary Data and Biometric Features

<b>Background/Objectives:</b> Electrocardiogram data are widely used to diagnose cardiovascular diseases, a leading cause of death globally. Traditional interpretation methods are manual, time-consuming, and prone to error. Machine learning offers a promising alternative for automating t...

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Bibliographic Details
Main Authors: Kennette James Basco, Alana Singh, Daniel Nasef, Christina Hartnett, Michael Ruane, Jason Tagliarino, Michael Nizich, Milan Toma
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Diagnostics
Subjects:
ECG/EKG
ECG-related biometrics
Extremely randomized trees
gradient boosted trees
support vector machines
Online Access:https://www.mdpi.com/2075-4418/15/7/903
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