The Construction of Smart Chinese Medicine Cloud Health Platform Based on Deep Neural Networks
In order to improve the efficiency of doctors’ diagnosis and treatment, the state has built a Chinese medicine cloud health platform. However, most medical institutions currently use internal networks, and the technical standards and specifications are not uniform. Some information is not compatible...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | International Transactions on Electrical Energy Systems |
| Online Access: | http://dx.doi.org/10.1155/2022/6751915 |
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| Summary: | In order to improve the efficiency of doctors’ diagnosis and treatment, the state has built a Chinese medicine cloud health platform. However, most medical institutions currently use internal networks, and the technical standards and specifications are not uniform. Some information is not compatible and patient information cannot be shared. Therefore, the construction of a smart traditional Chinese medicine (TCM) cloud health platform based on deep neural networks has become a current research hotspot. The research results show that the deep neural network technology has a theoretical basis and feasibility in the smart Chinese medicine cloud health platform. Combining with deep neural network technology, a cloud-based Chinese medicine cloud health system has been developed through big data analysis technology. Through the investigation and research method, this paper found that the smart Chinese medicine cloud health platform based on deep neural networks was more popular with citizens, which could improve the quality and efficiency of management. The average management quality of a smart TCM health cloud platform based on deep neural networks was 81.1, and the average management quality of a common TCM cloud health platform was 75. The efficiency of the smart Chinese medicine cloud health platform based on deep neural networks was relatively stable, with an average of 84%. The efficiency of the general TCM cloud health platform fluctuated significantly and was relatively unstable, with an average of 73.5%. The efficiency of the smart Chinese medicine cloud health platform was 10.5% higher than that of the ordinary Chinese medicine cloud health platform. This shows that the construction of the intelligent Chinese medicine cloud health platform under the deep neural network is relatively successful. |
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| ISSN: | 2050-7038 |