Enhanced Cardiovascular Disease Prediction Modelling using Machine Learning Techniques: A Focus on CardioVitalnet-Reference-Cited by-同舟云学术

Enhanced Cardiovascular Disease Prediction Modelling using Machine Learning Techniques: A Focus on CardioVitalnet

Published:2024-04-16 Issue: Volume: Page:1-33
ISSN:0954-898X
Container-title:Network: Computation in Neural Systems
language:en
Short-container-title:Network: Computation in Neural Systems

Author:

Ejiyi Chukwuebuka Joseph¹,Qin Zhen¹,Nneji Grace Ugochi²,Monday Happy Nkanta²,Agbesi Victor K.³,Ejiyi Makuachukwu Bennedith⁴,Ejiyi Thomas Ugochukwu⁵,Bamisile Olusola O.⁶

Affiliation:

1. Network and Data Security Key Laboratory, University of Electronic Science and Technology of China, Chengdu, Sichuan, China

2. Department of Computer Science and Software Engineering, Oxford Brookes College of Chengdu University of Technology, China

3. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

4. Pharmacy Department, University of Nigeria Nsukka, Enugu, Nigeria

5. Department of Pure and Industrial Chemistry, University of Nigeria Nsukka, Enugu, Nigeria

6. Sichuan Industrial Internet Intelligent Monitoring and Application Engineering Research Center, Chengdu University of Technology, Chengdu, China

Funder

National Natural Science Foundation of China

Sichuan Science and Technology Innovation Platform and Talent Plan

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0954898X.2024.2343341

Reference31 articles.

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2. ARTIFICIAL INTELLIGENCE APPLIED TO ECG IMPROVES HEART FAILURE PREDICTION ACCURACY

3. Heart disease prediction using supervised machine learning algorithms: Performance analysis and comparison

4. Comprehensive assessment, review, and comparison of AI models for solar irradiance prediction based on different time/estimation intervals

5. Comparison of machine learning and deep learning algorithms for hourly global/diffuse solar radiation predictions

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