Optimization of the Medical Service Consultation System Based on the Artificial Intelligence of the Internet of Things | |
Mao, Yi1![]() ![]() | |
2021 | |
发表期刊 | IEEE Access
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ISSN | 2169-3536 |
EISSN | 2169-3536 |
卷号 | 9页码:98261-98274 |
摘要 | Artificial intelligence-assisted diagnosis systems are developing rapidly, but doctors are currently less aware of artificial intelligence-assisted diagnosis systems. Understanding how to allow doctors to accept and use artificial intelligence medical assistant diagnosis system can promote the implementation of artificial intelligence medical assistant diagnosis system applications. Taking into account the current difficulties faced by the Internet of Things medical consultation services, this paper proposes a business operation model based on multi-party participation and sharing of medical consultation resources. We designed the information flow, overall logic and service implementation process of the service model, and completed the construction of the artificial intelligence medical service service model. We combine IoT technology to build a vital signs monitoring environment and clarify how to use IoT devices. In the error backpropagation algorithm, there is no significant difference in the contribution of different samples to the weight change, which makes the adjustment of network parameters not easily affected by difficult medical consultation samples, thereby weakening the effect of network medical consultation. In order to solve this problem, this article defines the degree to which the sample belongs to its correct category as the confidence of medical inquiry, and divides the training sample into a dangerous sample and a safe sample according to a dynamic threshold. Based on the difficulty of medical inquiry, an improved new learning algorithm is proposed. The algorithm penalizes the loss of dangerous samples, so that the convolutional neural network pays more attention to dangerous samples and can learn more effective information. Aiming at the eight physiological characteristics of data, this paper adjusts the structure of the convolutional neural network to make it take into account the richness of data characteristics and the dynamics of data changes over time. The realized CNN optimization algorithm model has improved the prediction effect, and the accuracy rate of medical consultation reaches 90.15%, which is better than other machine learning algorithms. © 2013 IEEE. |
关键词 | Backpropagation Convolution Convolutional neural networks Internet of things Patient monitoring Consultation services Data characteristics Error backpropagation algorithms Implementation process Network parameters Optimization algorithms Physiological characteristics Vital signs monitoring |
DOI | 10.1109/ACCESS.2021.3096188 |
收录类别 | EI ; SCIE |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications |
WOS记录号 | WOS:000673272100001 |
出版者 | Institute of Electrical and Electronics Engineers Inc. |
EI入藏号 | 20213010669497 |
EI分类号 | 461.6 Medicine and Pharmacology ; 716.1 Information Theory and Signal Processing ; 723 Computer Software, Data Handling and Applications ; 723.4 Artificial Intelligence |
原始文献类型 | Journal article (JA) |
出版地 | PISCATAWAY |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | https://ir.cqcet.edu.cn/handle/39TD4454/3197 |
专题 | 智慧健康学院 |
作者单位 | 1.School of Electronics and Internet of Things, Chongqing College of Electronic Engineering, Chongqing; 401331, China; 2.School of Smart Health, Chongqing College of Electronic Engineering, Chongqing; 401331, China |
第一作者单位 | 重庆电子科技职业大学 |
推荐引用方式 GB/T 7714 | Mao, Yi,Zhang, Lei. Optimization of the Medical Service Consultation System Based on the Artificial Intelligence of the Internet of Things[J]. IEEE Access,2021,9:98261-98274. |
APA | Mao, Yi,&Zhang, Lei.(2021).Optimization of the Medical Service Consultation System Based on the Artificial Intelligence of the Internet of Things.IEEE Access,9,98261-98274. |
MLA | Mao, Yi,et al."Optimization of the Medical Service Consultation System Based on the Artificial Intelligence of the Internet of Things".IEEE Access 9(2021):98261-98274. |
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