Psychiatry Research, volume 327, pages 115265

An overview of clustering methods with guidelines for application in mental health research

Gao Caroline X. ^{1, 2, 3}

Dwyer Dominic E ^{2, 3}

Zhu Ye ⁴

Smith Cathy M. ¹

Du Lan ⁵

Filia Kate M. ^{2, 3}

Bayer Johanna ^{2, 3}

Menssink Jana M. ^{2, 3}

Wang Teresa ⁵

Bergmeir Christoph ^{5, 6}

Wood S J ^{2, 3}

Cotton S. ^{2, 3}

Hide authors affiliations Show authors affiliations: 6 affiliations

Department of Epidemiology and Preventative Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia |

Orygen, Parkville, VIC, Australia |

Centre for Youth Mental Health, The University of Melbourne, Parkville, VIC, Australia |

⁴

School of Information Technology, Deakin University, Geelong, VIC, Australia |

⁵

Faculty of Information Technology, Monash University, Clayton, VIC, Australia |

⁶

Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain |

Publication type: Journal Article

Publication date: 2023-09-01

Elsevier

Journal: Psychiatry Research

Quartile SCImago

Quartile WOS

Impact factor: 11.3

ISSN: 01651781, 18727123

DOI: 10.1016/j.psychres.2023.115265

Copy DOI

Psychiatry and Mental health

Biological Psychiatry

Abstract

Cluster analyzes have been widely used in mental health research to decompose inter-individual heterogeneity by identifying more homogeneous subgroups of individuals. However, despite advances in new algorithms and increasing popularity, there is little guidance on model choice, analytical framework and reporting requirements. In this paper, we aimed to address this gap by introducing the philosophy, design, advantages/disadvantages and implementation of major algorithms that are particularly relevant in mental health research. Extensions of basic models, such as kernel methods, deep learning, semi-supervised clustering, and clustering ensembles are subsequently introduced. How to choose algorithms to address common issues as well as methods for pre-clustering data processing, clustering evaluation and validation are then discussed. Importantly, we also provide general guidance on clustering workflow and reporting requirements. To facilitate the implementation of different algorithms, we provide information on R functions and libraries.

By date By citations

Citations by journals

	1
WSEAS Transactions on Mathematics	WSEAS Transactions on Mathematics, 1, 33.33% WSEAS Transactions on Mathematics 1 publication, 33.33%
IEEE Access	IEEE Access, 1, 33.33% IEEE Access 1 publication, 33.33%
Lingua	Lingua, 1, 33.33% Lingua 1 publication, 33.33%
	1

Citations by publishers

	1
World Scientific and Engineering Academy and Society (WSEAS)	World Scientific and Engineering Academy and Society (WSEAS), 1, 33.33% World Scientific and Engineering Academy and Society (WSEAS) 1 publication, 33.33%
IEEE	IEEE, 1, 33.33% IEEE 1 publication, 33.33%
Elsevier	Elsevier, 1, 33.33% Elsevier 1 publication, 33.33%
	1

We do not take into account publications that without a DOI.
Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
Statistics recalculated weekly.

{"yearsCitations":{"type":"bar","data":{"show":true,"labels":[2023,2024],"ids":[0,0],"codes":[0,0],"imageUrls":["",""],"datasets":[{"label":"Citations number","data":[2,1],"backgroundColor":["#3B82F6","#3B82F6"],"percentage":["66.67","33.33"],"barThickness":null}]},"options":{"indexAxis":"x","maintainAspectRatio":true,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":1,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Citations per year","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"journals":{"type":"bar","data":{"show":true,"labels":["WSEAS Transactions on Mathematics","IEEE Access","Lingua"],"ids":[14516,25260,18156],"codes":[0,0,0],"imageUrls":["","\/storage\/images\/resized\/6scCJegesojp2jubwY3uKCzTAmgsaH2GIFlg6Hfk_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp"],"datasets":[{"label":"","data":[1,1,1],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6"],"percentage":[33.33,33.33,33.33],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Journals","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}},"publishers":{"type":"bar","data":{"show":true,"labels":["World Scientific and Engineering Academy and Society (WSEAS)","IEEE","Elsevier"],"ids":[9122,6953,17],"codes":[0,0,0],"imageUrls":["","\/storage\/images\/resized\/6scCJegesojp2jubwY3uKCzTAmgsaH2GIFlg6Hfk_medium.webp","\/storage\/images\/resized\/GDnYOu1UpMMfMMRV6Aqle4H0YLLsraeD9IP9qScG_medium.webp"],"datasets":[{"label":"","data":[1,1,1],"backgroundColor":["#3B82F6","#3B82F6","#3B82F6"],"percentage":[33.33,33.33,33.33],"barThickness":13}]},"options":{"indexAxis":"y","maintainAspectRatio":false,"scales":{"y":{"ticks":{"precision":0,"autoSkip":false,"font":{"family":"Montserrat"},"color":"#000000"}},"x":{"ticks":{"stepSize":null,"precision":0,"font":{"family":"Montserrat"},"color":"#000000"}}},"plugins":{"legend":{"position":"top","labels":{"font":{"family":"Montserrat"},"color":"#000000"}},"title":{"display":true,"text":"Publishers","font":{"size":24,"family":"Montserrat","weight":600},"color":"#000000"}}}}}

Metrics

Cite this

GOST |

Cite this

GOST Copy

Gao C. X. et al. An overview of clustering methods with guidelines for application in mental health research // Psychiatry Research. 2023. Vol. 327. p. 115265.

GOST all authors (up to 50) Copy

Gao C. X., Dwyer D. E., Zhu Y., Smith C. M., Du L., Filia K. M., Bayer J., Menssink J. M., Wang T., Bergmeir C., Wood S. J., Cotton S. An overview of clustering methods with guidelines for application in mental health research // Psychiatry Research. 2023. Vol. 327. p. 115265.

RIS |

Cite this

RIS Copy

TY - JOUR

DO - 10.1016/j.psychres.2023.115265

UR - https://doi.org/10.1016%2Fj.psychres.2023.115265

TI - An overview of clustering methods with guidelines for application in mental health research

T2 - Psychiatry Research

AU - Gao, Caroline X.

AU - Dwyer, Dominic E

AU - Zhu, Ye

AU - Smith, Cathy M.

AU - Du, Lan

AU - Filia, Kate M.

AU - Bayer, Johanna

AU - Menssink, Jana M.

AU - Wang, Teresa

AU - Bergmeir, Christoph

AU - Wood, S J

AU - Cotton, S.

PY - 2023

DA - 2023/09/01 00:00:00

PB - Elsevier

SP - 115265

VL - 327

SN - 0165-1781

SN - 1872-7123

ER -

BibTex

Cite this

BibTex Copy

@article{2023_Gao,

author = {Caroline X. Gao and Dominic E Dwyer and Ye Zhu and Cathy M. Smith and Lan Du and Kate M. Filia and Johanna Bayer and Jana M. Menssink and Teresa Wang and Christoph Bergmeir and S J Wood and S. Cotton},

title = {An overview of clustering methods with guidelines for application in mental health research},

journal = {Psychiatry Research},

year = {2023},

volume = {327},

publisher = {Elsevier},

month = {sep},

url = {https://doi.org/10.1016%2Fj.psychres.2023.115265},

pages = {115265},

doi = {10.1016/j.psychres.2023.115265}

}

Found error?

Publisher

Elsevier

Journal

Psychiatry Research

Quartile SCImago

Quartile WOS

Impact factor

11.3

ISSN

01651781 (Print)
18727123 (Electronic)