Gradient boosting machine model predicts psychiatric complications after deep brain stimulation in Parkinson’s disease

doi:10.5498/wjp.v16.i2.113124

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 16, Issue 2

This Article

(42)

(37)

(0)

(635)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Psychiatry

ISSN

2220-3206

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

World J Psychiatry. Feb 19, 2026; 16(2): 113124
Published online Feb 19, 2026. doi: 10.5498/wjp.v16.i2.113124

Table 3 Comparison of preoperative-related scale scores, mean ± SD

Items	Complication group (69 cases)	Non-complication group (94 cases)	t value	P value
PSQI score	10.57 ± 1.98	8.62 ± 2.32	5.630	< 0.001
H-FRAT score	28.94 ± 3.15	32.86 ± 4.81	6.274	< 0.001
PDQ-39 score	74.81 ± 8.97	70.78 ± 11.42	2.434	0.016
UPDRS III score	42.65 ± 5.00	38.09 ± 4.65	6.002	< 0.001

PSQI: Pittsburgh Sleep Quality Index; H-FRAT: Family Relationship Health Assessment Scale; PDQ-39: 39-item Parkinson’s Disease Questionnaire; UPDRS III: Unified Parkinson’s Disease Rating Scale Part III.

Full Size Table

Citation: Liao S, Tang JW, Li Y. Gradient boosting machine model predicts psychiatric complications after deep brain stimulation in Parkinson’s disease. World J Psychiatry 2026; 16(2): 113124
URL: https://www.wjgnet.com/2220-3206/full/v16/i2/113124.htm
DOI: https://dx.doi.org/10.5498/wjp.v16.i2.113124

Liao S, Tang JW, Li Y. Gradient boosting machine model predicts psychiatric complications after deep brain stimulation in Parkinson’s disease. World J Psychiatry 2026; 16(2): 113124 [PMID: 41641213 DOI: 10.5498/wjp.v16.i2.113124]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.