Abstract
This article mainly focuses on the preprocessing method of medical heterogeneous equipment health data sources and the performance measurement of single-layer perceptron network intelligent computing. It structures a data quality evaluation system of medical heterogeneous equipment with five different dimensions: patient personal information, medical basic data, medical testing data, medical treatment data and medical device data. An innovative preprocessing algorithm of data sources is proposed to study the missing data, the error data, the repetition data and the validity data. By constructing a single-layer perceptron network, accuracy, misjudgment rate, precision, recall, true positive rate and false positive rate in intelligent computing are studied, and the corresponding mathematical calculation formulas are established. In the application research, this article collected 157 original data from a medical institution. The algorithm is applied and the models are tested. The research solved the problems of intelligent computing performance measurement of heterogeneous devices based on single-layer perceptron network.
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The data in this paper are from the Guangdong Second Provincial General Hospital, China. However, because the patients are protected by law in China, the data cannot be provided to any third party.
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Acknowledgements
The major science and technology project of Guangzhou’s R & D plan in key areas is “Guangzhou national new generation artificial intelligence innovation and development pilot zone artificial intelligence social experiment unveiling project” (Guangzhou 2022-06-01).
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Qu, H., Lian, W., Pang, S. et al. Five-dimensional evaluation system and perceptron intelligent computing performance measurement methods based on medical heterogeneous equipment health data. Neural Comput & Applic 35, 24651–24664 (2023). https://doi.org/10.1007/s00521-023-08316-3
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DOI: https://doi.org/10.1007/s00521-023-08316-3