Analysis and processing of misdiagnosis data for depression based on modified entropy weight method

Analysis and processing of misdiagnosis data for depression based on modified entropy weight method

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 in...

Full description

Bibliographic Details
Main Authors: Shiying Lu, Ji’an Tang, Feng Liu, Sishi Qin, Jie Chen, Lei Chen
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/74/e3sconf_ebldm2020_03033.pdf
id doaj-a2f3d4699ae54a9c8a85d2821187a8fc
record_format Article
spelling doaj-a2f3d4699ae54a9c8a85d2821187a8fc2021-04-02T16:02:29ZengEDP SciencesE3S Web of Conferences2267-12422020-01-012140303310.1051/e3sconf/202021403033e3sconf_ebldm2020_03033Analysis and processing of misdiagnosis data for depression based on modified entropy weight methodShiying Lu0Ji’an Tang1Feng Liu2Sishi Qin3Jie Chen4Lei Chen5Changsha university of science and technologyShanghai University of International, Business and EconomicsInstitute of Artificial Intelligence and Change Management/Shanghai University of International Business and EconomicsShanghai University of International, Business and EconomicsChangshu Institute of TechnologyWuxi Prithink Information Technology Co., Ltd.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.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/74/e3sconf_ebldm2020_03033.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Shiying Lu
Ji’an Tang
Feng Liu
Sishi Qin
Jie Chen
Lei Chen
spellingShingle Shiying Lu
Ji’an Tang
Feng Liu
Sishi Qin
Jie Chen
Lei Chen
Analysis and processing of misdiagnosis data for depression based on modified entropy weight method
E3S Web of Conferences
author_facet Shiying Lu
Ji’an Tang
Feng Liu
Sishi Qin
Jie Chen
Lei Chen
author_sort Shiying Lu
title Analysis and processing of misdiagnosis data for depression based on modified entropy weight method
title_short Analysis and processing of misdiagnosis data for depression based on modified entropy weight method
title_full Analysis and processing of misdiagnosis data for depression based on modified entropy weight method
title_fullStr Analysis and processing of misdiagnosis data for depression based on modified entropy weight method
title_full_unstemmed Analysis and processing of misdiagnosis data for depression based on modified entropy weight method
title_sort analysis and processing of misdiagnosis data for depression based on modified entropy weight method
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description 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.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/74/e3sconf_ebldm2020_03033.pdf
work_keys_str_mv AT shiyinglu analysisandprocessingofmisdiagnosisdatafordepressionbasedonmodifiedentropyweightmethod
AT jiantang analysisandprocessingofmisdiagnosisdatafordepressionbasedonmodifiedentropyweightmethod
AT fengliu analysisandprocessingofmisdiagnosisdatafordepressionbasedonmodifiedentropyweightmethod
AT sishiqin analysisandprocessingofmisdiagnosisdatafordepressionbasedonmodifiedentropyweightmethod
AT jiechen analysisandprocessingofmisdiagnosisdatafordepressionbasedonmodifiedentropyweightmethod
AT leichen analysisandprocessingofmisdiagnosisdatafordepressionbasedonmodifiedentropyweightmethod
_version_ 1721558202236010496

Similar Items