| Issue |
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|
|
|---|---|---|
| Article Number | 03033 | |
| Number of page(s) | 5 | |
| Section | Digital Development and Environmental Management of Energy Supply Chain | |
| DOI | https://doi.org/10.1051/e3sconf/202021403033 | |
| Published online | 07 December 2020 | |
Analysis and processing of misdiagnosis data for depression based on modified entropy weight method
1 Changsha university of science and technology, Hunan China
2 Shanghai University of International, Business and Economics, Shanghai China
3 Institute of Artificial Intelligence and Change Management/Shanghai University of International Business and Economics
4 Shanghai University of International, Business and Economics, Shanghai China
5 Changshu Institute of Technology, Jiangsu China
6 Wuxi Prithink Information Technology Co., Ltd., Jiangsu China
a 529455452@qq.com
b 2513217525@qq.com
c lsttoy@163.com
d 1034109212@qq.com
e natsusu@qq.com
f 757076251@qq.com
Depression is always the core field of psychological research, and the analysis of misdiagnosis data of depression is also the vital content of depression research. Based on the analysis of misdiagnosis data processing, this paper adopts a order relation analysis method, to correct the problem of inconsistent entropy and entropy transfer relation (when all entropy value tend to be 1). This paper obtains multi-index comprehensive quantitative values, from various angles analysis of misdiagnosis data depression, so as to avoid subjective and one-sided evaluation results. It not only improves the rapidity and practicability of the algorithm, but also makes the analysis of misdiagnosis data more objective and accurate, which can be applied to medical field.
© The Authors, published by EDP Sciences, 2020
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