Abstract
This paper presents a BP neural network-based algorithm for the identification of coronary heart disease through the clinical data of cardiology for many years and the personal physiological attributes easily obtained in daily life. The goal of this paper is to judge whether it may have coronary heart disease by testing the attribute values of the tester. First, through the training of samples, the network model structure is designed, and a relatively good neural network model is obtained. Second, according to the model, the possibility of coronary heart disease was calculated.
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YanHui Fang performed the computer simulations. Wei Fang, YanHui Fang and WeiZhen Yang analysed the data. Wei Fang wrote the original draft. YanHui Fang and WeiZhen Yang revised and edited the manuscript. YanHui Fang edited the manuscript. All authors confirmed the submitted version.
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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Fang, Y., Fang, W., Yang, W. (2023). Application of Neural Networks in Early Warning Systems for Coronary Heart Disease. In: Yu, Z., et al. Data Science. ICPCSEE 2023. Communications in Computer and Information Science, vol 1880. Springer, Singapore. https://doi.org/10.1007/978-981-99-5971-6_3
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DOI: https://doi.org/10.1007/978-981-99-5971-6_3
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-99-5971-6
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