Abstract
As intelligent computing has been an important application in the medical field, there are more and more examples of smart medical technology improving healthcare services. Smart medical technology is a kind of artificial intelligence diagnostic technology that can simulate the diagnosis experience of medical experts and combine the thinking process of medical knowledge through the study and analysis of data. With the help of machine learning algorithms, doctors can diagnose different kinds of diseases more conveniently and accurately, which conforms to the needs of modern society’s developments. Smart medical technology can effectively solve shortage problems of medical resources and inexperience of young doctors, and reduce the labor intensity of medical staffs. It can make a more scientific and objective diagnosis and can expand the database by keeping collecting data and truly keeping up with the times. At the same time, it also provides scientific experts with better auxiliary functions and better solutions and generate positive guidance and influence for people’s future lifestyles through the analysis of attribute indicators. In this paper, several intelligent computing methods are selected to model and analyze the epileptic EEG signal dataset and thyroid dataset, establish their respective classification models by parameter optimizations, find out the most suitable intelligent computing classification algorithms by comparing a series of parameter indicators, analyze the advantages and disadvantages of these algorithms, and provide selection suggestions.
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Wang, S., Jiang, Y. (2021). Exploration of Smart Medical Technology Based on Intelligent Computing Methods. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12837. Springer, Cham. https://doi.org/10.1007/978-3-030-84529-2_24
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DOI: https://doi.org/10.1007/978-3-030-84529-2_24
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