Semantic processing of personality description for depression patients

Zhisheng Huang; Qing Hu; Haiyuan Wang; Yahan Zhang; Jie Yang; Gang Wang

doi:10.1007/978-3-030-32962-4_24

Semantic processing of personality description for depression patients

Zhisheng Huang, Qing Hu, Haiyuan Wang, Yahan Zhang, Jie Yang, Gang Wang^*

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

The personality description has been considered to be an important part of the electronic medical records (EMRs) for depression in-patients. However, the personality description of a patient is usually provided by a family member of the patient when he or she is admitted to the hospital. Because of non-professional background of those family members, personality descriptions in EMRS have various problems such as non-standard description, confusion between personality and behavior, and others. In this paper, we propose an approach to dealing with non-standard description of personality for depression patients by introducing a semantic relevance measure of personality. Furthermore, we make a mapping of those personality description items into the personality items in the well-known personality model of the Sixteen Personality Factor Questionnaire (16PF). We find some interesting observations on the connection between existing personality description in EMRs and the personality items in the 16PF model, and suggest possible improvement of the personality description in EMRs for depression patients.

Original language	English
Title of host publication	Health Information Science
Subtitle of host publication	8th International Conference, HIS 2019, Xi'an, China, October 18–20, 2019, Proceedings
Editors	Hua Wang, Siuly Siuly, Yanchun Zhang, Rui Zhou, Fernando Martin-Sanchez, Zhisheng Huang
Publisher	Springer
Pages	263-275
Number of pages	13
ISBN (Electronic)	9783030329624
ISBN (Print)	9783030329617
DOIs	https://doi.org/10.1007/978-3-030-32962-4_24
Publication status	Published - 2019
Event	8th International Conference on Health Information Science, HIS 2019 - Xi'an, China Duration: 18 Oct 2019 → 20 Oct 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11837 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Health Information Science, HIS 2019
Country	China
City	Xi'an
Period	18/10/19 → 20/10/19

Keywords

16 Personality Factor (16PF)
Depression
Personality
Semantic processing
Semantic relevance measure

Access to Document

10.1007/978-3-030-32962-4_24

Cite this

Huang, Z., Hu, Q., Wang, H., Zhang, Y., Yang, J., & Wang, G. (2019). Semantic processing of personality description for depression patients. In H. Wang, S. Siuly, Y. Zhang, R. Zhou, F. Martin-Sanchez, & Z. Huang (Eds.), Health Information Science: 8th International Conference, HIS 2019, Xi'an, China, October 18–20, 2019, Proceedings (pp. 263-275). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11837 LNCS). Springer. https://doi.org/10.1007/978-3-030-32962-4_24

Huang, Zhisheng ; Hu, Qing ; Wang, Haiyuan ; Zhang, Yahan ; Yang, Jie ; Wang, Gang. / Semantic processing of personality description for depression patients. Health Information Science: 8th International Conference, HIS 2019, Xi'an, China, October 18–20, 2019, Proceedings. editor / Hua Wang ; Siuly Siuly ; Yanchun Zhang ; Rui Zhou ; Fernando Martin-Sanchez ; Zhisheng Huang. Springer, 2019. pp. 263-275 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{0273fec786cf417286525eed895fcc1e,

title = "Semantic processing of personality description for depression patients",

abstract = "The personality description has been considered to be an important part of the electronic medical records (EMRs) for depression in-patients. However, the personality description of a patient is usually provided by a family member of the patient when he or she is admitted to the hospital. Because of non-professional background of those family members, personality descriptions in EMRS have various problems such as non-standard description, confusion between personality and behavior, and others. In this paper, we propose an approach to dealing with non-standard description of personality for depression patients by introducing a semantic relevance measure of personality. Furthermore, we make a mapping of those personality description items into the personality items in the well-known personality model of the Sixteen Personality Factor Questionnaire (16PF). We find some interesting observations on the connection between existing personality description in EMRs and the personality items in the 16PF model, and suggest possible improvement of the personality description in EMRs for depression patients.",

keywords = "16 Personality Factor (16PF), Depression, Personality, Semantic processing, Semantic relevance measure",

author = "Zhisheng Huang and Qing Hu and Haiyuan Wang and Yahan Zhang and Jie Yang and Gang Wang",

year = "2019",

doi = "10.1007/978-3-030-32962-4_24",

language = "English",

isbn = "9783030329617",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "263--275",

editor = "Hua Wang and Siuly Siuly and Yanchun Zhang and Rui Zhou and Fernando Martin-Sanchez and Zhisheng Huang",

booktitle = "Health Information Science",

note = "8th International Conference on Health Information Science, HIS 2019 ; Conference date: 18-10-2019 Through 20-10-2019",

}

Huang, Z, Hu, Q, Wang, H, Zhang, Y, Yang, J & Wang, G 2019, Semantic processing of personality description for depression patients. in H Wang, S Siuly, Y Zhang, R Zhou, F Martin-Sanchez & Z Huang (eds), Health Information Science: 8th International Conference, HIS 2019, Xi'an, China, October 18–20, 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11837 LNCS, Springer, pp. 263-275, 8th International Conference on Health Information Science, HIS 2019, Xi'an, China, 18/10/19. https://doi.org/10.1007/978-3-030-32962-4_24

Semantic processing of personality description for depression patients. / Huang, Zhisheng; Hu, Qing; Wang, Haiyuan; Zhang, Yahan; Yang, Jie; Wang, Gang.

Health Information Science: 8th International Conference, HIS 2019, Xi'an, China, October 18–20, 2019, Proceedings. ed. / Hua Wang; Siuly Siuly; Yanchun Zhang; Rui Zhou; Fernando Martin-Sanchez; Zhisheng Huang. Springer, 2019. p. 263-275 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11837 LNCS).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Semantic processing of personality description for depression patients

AU - Huang, Zhisheng

AU - Hu, Qing

AU - Wang, Haiyuan

AU - Zhang, Yahan

AU - Yang, Jie

AU - Wang, Gang

PY - 2019

Y1 - 2019

N2 - The personality description has been considered to be an important part of the electronic medical records (EMRs) for depression in-patients. However, the personality description of a patient is usually provided by a family member of the patient when he or she is admitted to the hospital. Because of non-professional background of those family members, personality descriptions in EMRS have various problems such as non-standard description, confusion between personality and behavior, and others. In this paper, we propose an approach to dealing with non-standard description of personality for depression patients by introducing a semantic relevance measure of personality. Furthermore, we make a mapping of those personality description items into the personality items in the well-known personality model of the Sixteen Personality Factor Questionnaire (16PF). We find some interesting observations on the connection between existing personality description in EMRs and the personality items in the 16PF model, and suggest possible improvement of the personality description in EMRs for depression patients.

AB - The personality description has been considered to be an important part of the electronic medical records (EMRs) for depression in-patients. However, the personality description of a patient is usually provided by a family member of the patient when he or she is admitted to the hospital. Because of non-professional background of those family members, personality descriptions in EMRS have various problems such as non-standard description, confusion between personality and behavior, and others. In this paper, we propose an approach to dealing with non-standard description of personality for depression patients by introducing a semantic relevance measure of personality. Furthermore, we make a mapping of those personality description items into the personality items in the well-known personality model of the Sixteen Personality Factor Questionnaire (16PF). We find some interesting observations on the connection between existing personality description in EMRs and the personality items in the 16PF model, and suggest possible improvement of the personality description in EMRs for depression patients.

KW - 16 Personality Factor (16PF)

KW - Depression

KW - Personality

KW - Semantic processing

KW - Semantic relevance measure

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SN - 9783030329617

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Health Information Science

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A2 - Zhang, Yanchun

A2 - Zhou, Rui

A2 - Martin-Sanchez, Fernando

A2 - Huang, Zhisheng

PB - Springer

T2 - 8th International Conference on Health Information Science, HIS 2019

Y2 - 18 October 2019 through 20 October 2019

ER -

Huang Z, Hu Q, Wang H, Zhang Y, Yang J, Wang G. Semantic processing of personality description for depression patients. In Wang H, Siuly S, Zhang Y, Zhou R, Martin-Sanchez F, Huang Z, editors, Health Information Science: 8th International Conference, HIS 2019, Xi'an, China, October 18–20, 2019, Proceedings. Springer. 2019. p. 263-275. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-32962-4_24

Semantic processing of personality description for depression patients

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Keywords

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