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

IF 1.1 3区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Network-Computation in Neural Systems Pub Date : 2024-04-16 DOI:10.1080/0954898x.2024.2343341
Chukwuebuka Joseph Ejiyi, Zhen Qin, Grace Ugochi Nneji, Happy Nkanta Monday, Victor K. Agbesi, Makuachukwu Bennedith Ejiyi, Thomas Ugochukwu Ejiyi, Olusola O. Bamisile
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Abstract

Aiming at early detection and accurate prediction of cardiovascular disease (CVD) to reduce mortality rates, this study focuses on the development of an intelligent predictive system to identify in...
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利用机器学习技术增强心血管疾病预测建模:聚焦心血管网络
为了及早发现和准确预测心血管疾病(CVD)以降低死亡率,本研究重点开发了一种智能预测系统,以识别心血管疾病的早期症状。
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来源期刊
Network-Computation in Neural Systems
Network-Computation in Neural Systems 工程技术-工程:电子与电气
CiteScore
3.70
自引率
1.30%
发文量
22
审稿时长
>12 weeks
期刊介绍: Network: Computation in Neural Systems welcomes submissions of research papers that integrate theoretical neuroscience with experimental data, emphasizing the utilization of cutting-edge technologies. We invite authors and researchers to contribute their work in the following areas: Theoretical Neuroscience: This section encompasses neural network modeling approaches that elucidate brain function. Neural Networks in Data Analysis and Pattern Recognition: We encourage submissions exploring the use of neural networks for data analysis and pattern recognition, including but not limited to image analysis and speech processing applications. Neural Networks in Control Systems: This category encompasses the utilization of neural networks in control systems, including robotics, state estimation, fault detection, and diagnosis. Analysis of Neurophysiological Data: We invite submissions focusing on the analysis of neurophysiology data obtained from experimental studies involving animals. Analysis of Experimental Data on the Human Brain: This section includes papers analyzing experimental data from studies on the human brain, utilizing imaging techniques such as MRI, fMRI, EEG, and PET. Neurobiological Foundations of Consciousness: We encourage submissions exploring the neural bases of consciousness in the brain and its simulation in machines.
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