Personalized LSTM Models for ECG Lead Transformations Led to Fewer Diagnostic Errors Than Generalized Models: Deriving 12-Lead ECG from Lead II, V2, and V6

Personalized LSTM Models for ECG Lead Transformations Led to Fewer Diagnostic Errors Than Generalized Models: Deriving 12-Lead ECG from Lead II, V2, and V6

Background and Objective: The prevalence of chronic cardiovascular diseases (CVDs) has risen globally, nearly doubling from 1990 to 2019. ECG is a simple, non-invasive measurement that can help identify CVDs at an early and treatable stage. A multi-lead ECG, up to 15 leads in a wearable form factor,...

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Bibliographic Details
Main Authors: Prashanth Shyam Kumar, Mouli Ramasamy, Kamala Ramya Kallur, Pratyush Rai, Vijay K. Varadan
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
ECG
LSTM networks
Bayesian Optimization
personalized medicine
wearable devices
Online Access:https://www.mdpi.com/1424-8220/23/3/1389

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https://www.mdpi.com/1424-8220/23/3/1389

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