A two-stage deep CNN architecture for the classification of low-risk and high-risk hypertension classes using multi-lead ECG signals

A two-stage deep CNN architecture for the classification of low-risk and high-risk hypertension classes using multi-lead ECG signals

Hypertension pathology is the increase in blood pressure which may cause cardiac, neural, and kidney diseases. Hence, it is very important to detect and treat hypertension as early as possible. In clinical standards, the monitoring of 24 h of ambulatory recording of the blood pressure signal is used...

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Bibliographic Details
Main Authors: Piyush Jain, Pranjali Gajbhiye, R.K. Tripathy, U. Rajendra Acharya
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:Informatics in Medicine Unlocked
Subjects:
Hypertension
Multilead ECG
Convolutional neural network
Cross-validation
Accuracy
Online Access:http://www.sciencedirect.com/science/article/pii/S2352914820306304

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http://www.sciencedirect.com/science/article/pii/S2352914820306304

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