Effective Hypertension Detection Using Predictive Feature Engineering and Deep Learning-Reference-Cited by-同舟云学术

Effective Hypertension Detection Using Predictive Feature Engineering and Deep Learning

Published:2024 Issue: Volume:12 Page:89055-89068
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Abbas Sidra¹^ORCID,Avelino Sampedro Gabriel²^ORCID,Krichen Moez³^ORCID,Alamro Meznah A.⁴^ORCID,Mihoub Alaeddine⁵^ORCID,Kulhanek Rastislav⁶^ORCID

Affiliation:

1. Department of Computer Science, COMSATS University Islamabad, Islamabad, Pakistan

2. School of Management and Information Technology, De La Salle—College of Saint Benilde, Manila, Philippines

3. FCSIT, Al-Baha University, Al Bahah, Saudi Arabia

4. Department of Information Technology, College of Computer & Information Science, Princess Nourah Bint Abdul Rahman University, Riyadh, Saudi Arabia

5. Department of Management Information Systems and Production Management, College of Business and Economics, Qassim University, Buraydah, Saudi Arabia

6. Department of Information Management and Business Systems, Faculty of Management, Comenius University Bratislava, Bratislava, Slovakia

Funder

rincess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia, through the Researchers Supporting Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10570165.pdf?arnumber=10570165

Reference33 articles.

1. A novel technique for continuous blood pressure estimation from optimal feature set of PPG signal using deep learning approach;Raju,2023

2. “The Economic Burden of Hypertension”

3. ExHyptNet: An explainable diagnosis of hypertension using EfficientNet with PPG signals

4. Pressure natriuresis and the renal control of arterial blood pressure

5. Systemic considerations in the management of diabetic retinopathy