Computational objectivity in depression assessment for unstructured large datasets

Aaron Johnson; Paul Holmes; Lewis Craske; Marcello Trovati; Nik Bessis; Peter Larcombe

doi:10.1109/CIT/IUCC/DASC/PICOM.2015.308

Computational objectivity in depression assessment for unstructured large datasets

Aaron Johnson, Paul Holmes, Lewis Craske, Marcello Trovati, Nik Bessis, Peter Larcombe

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding (ISBN) › peer-review

Abstract

The Patient Health Questionnaire (PHQ-9) is the depression module, which provides a score correlating to each of the Depression Severity Measure (DSM-IV) criteria, whose output is a total score suggesting which category of depression a patient slots into. In this paper we propose a novel method to potentially improve the current system in place for health professionals in diagnosing depression. Thus, our objective is to propose a more computational method of measurement, similar to the PHQ-9 already in place, with a mathematical ranking system based on a large unstructured dataset consisting of abstracts available from PubMed.

Original language	English
Title of host publication	Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Editors	Luigi Atzori, Xiaolong Jin, Stephen Jarvis, Lei Liu, Ramon Aguero Calvo, Jia Hu, Geyong Min, Nektarios Georgalas, Yulei Wu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2075-2079
Number of pages	5
ISBN (Electronic)	9781509001545
DOIs	https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.308
Publication status	Published - 22 Dec 2015
Event	15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 - Liverpool, United Kingdom Duration: 26 Oct 2015 → 28 Oct 2015

Publication series

Name	Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

Conference

Conference	15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015
Country/Territory	United Kingdom
City	Liverpool
Period	26/10/15 → 28/10/15

Access to Document

10.1109/CIT/IUCC/DASC/PICOM.2015.308

Cite this

Johnson, A., Holmes, P., Craske, L., Trovati, M., Bessis, N., & Larcombe, P. (2015). Computational objectivity in depression assessment for unstructured large datasets. In L. Atzori, X. Jin, S. Jarvis, L. Liu, R. A. Calvo, J. Hu, G. Min, N. Georgalas, & Y. Wu (Eds.), Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 (pp. 2075-2079). Article 7363354 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.308

Johnson, Aaron ; Holmes, Paul ; Craske, Lewis et al. / Computational objectivity in depression assessment for unstructured large datasets. Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. editor / Luigi Atzori ; Xiaolong Jin ; Stephen Jarvis ; Lei Liu ; Ramon Aguero Calvo ; Jia Hu ; Geyong Min ; Nektarios Georgalas ; Yulei Wu. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2075-2079 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015).

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title = "Computational objectivity in depression assessment for unstructured large datasets",

abstract = "The Patient Health Questionnaire (PHQ-9) is the depression module, which provides a score correlating to each of the Depression Severity Measure (DSM-IV) criteria, whose output is a total score suggesting which category of depression a patient slots into. In this paper we propose a novel method to potentially improve the current system in place for health professionals in diagnosing depression. Thus, our objective is to propose a more computational method of measurement, similar to the PHQ-9 already in place, with a mathematical ranking system based on a large unstructured dataset consisting of abstracts available from PubMed.",

author = "Aaron Johnson and Paul Holmes and Lewis Craske and Marcello Trovati and Nik Bessis and Peter Larcombe",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015 ; Conference date: 26-10-2015 Through 28-10-2015",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2075--2079",

editor = "Luigi Atzori and Xiaolong Jin and Stephen Jarvis and Lei Liu and Calvo, {Ramon Aguero} and Jia Hu and Geyong Min and Nektarios Georgalas and Yulei Wu",

booktitle = "Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015",

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Johnson, A, Holmes, P, Craske, L, Trovati, M , Bessis, N & Larcombe, P 2015, Computational objectivity in depression assessment for unstructured large datasets. in L Atzori, X Jin, S Jarvis, L Liu, RA Calvo, J Hu, G Min, N Georgalas & Y Wu (eds), Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015., 7363354, Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, Institute of Electrical and Electronics Engineers Inc., pp. 2075-2079, 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015, Liverpool, United Kingdom, 26/10/15. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.308

Computational objectivity in depression assessment for unstructured large datasets. / Johnson, Aaron; Holmes, Paul; Craske, Lewis et al.
Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. ed. / Luigi Atzori; Xiaolong Jin; Stephen Jarvis; Lei Liu; Ramon Aguero Calvo; Jia Hu; Geyong Min; Nektarios Georgalas; Yulei Wu. Institute of Electrical and Electronics Engineers Inc., 2015. p. 2075-2079 7363354 (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding (ISBN) › peer-review

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AU - Holmes, Paul

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AU - Larcombe, Peter

PY - 2015/12/22

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AB - The Patient Health Questionnaire (PHQ-9) is the depression module, which provides a score correlating to each of the Depression Severity Measure (DSM-IV) criteria, whose output is a total score suggesting which category of depression a patient slots into. In this paper we propose a novel method to potentially improve the current system in place for health professionals in diagnosing depression. Thus, our objective is to propose a more computational method of measurement, similar to the PHQ-9 already in place, with a mathematical ranking system based on a large unstructured dataset consisting of abstracts available from PubMed.

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M3 - Conference proceeding (ISBN)

AN - SCOPUS:84964226763

T3 - Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

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A2 - Atzori, Luigi

A2 - Jin, Xiaolong

A2 - Jarvis, Stephen

A2 - Liu, Lei

A2 - Calvo, Ramon Aguero

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A2 - Min, Geyong

A2 - Georgalas, Nektarios

A2 - Wu, Yulei

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015

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Johnson A, Holmes P, Craske L, Trovati M , Bessis N, Larcombe P. Computational objectivity in depression assessment for unstructured large datasets. In Atzori L, Jin X, Jarvis S, Liu L, Calvo RA, Hu J, Min G, Georgalas N, Wu Y, editors, Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2075-2079. 7363354. (Proceedings - 15th IEEE International Conference on Computer and Information Technology, CIT 2015, 14th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2015, 13th IEEE International Conference on Dependable, Autonomic and Secure Computing, DASC 2015 and 13th IEEE International Conference on Pervasive Intelligence and Computing, PICom 2015). doi: 10.1109/CIT/IUCC/DASC/PICOM.2015.308

Computational objectivity in depression assessment for unstructured large datasets

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