Efficacy of a machine learning model integrating clinical-psychosocial factors in predicting posttraumatic bone nonunion and bone defects

doi:10.5498/wjp.119455

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 16, Issue 9

This Article

(2)

(0)

(2)

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

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Psychiatry. Sep 19, 2026; 16(9): 119455
Published online Sep 19, 2026. doi: 10.5498/wjp.119455

Table 4 Summary of internal validation model performance indicators for the development cohort

	Traditional clinical model	Integrated model
AUC (95%CI)	0.854 (0.788-0.919)	0.923 (0.856-0.990)
Sensitivity	0.588	0.882
Specificity	0.883	0.891
Accuracy	0.849	0.890
F1 score	0.476	0.640
DeLong’s test	-	P < 0.05

AUC: Area under the curve; CI: Confidence interval.

Full Size Table

Citation: Luan FF, Chen JY, Zheng YZ, Hu MH, Huang F, Zheng CX. Efficacy of a machine learning model integrating clinical-psychosocial factors in predicting posttraumatic bone nonunion and bone defects. World J Psychiatry 2026; 16(9): 119455
URL: https://www.wjgnet.com/2220-3206/full/v16/i9/119455.htm
DOI: https://dx.doi.org/10.5498/wjp.119455

Luan FF, Chen JY, Zheng YZ, Hu MH, Huang F, Zheng CX. Efficacy of a machine learning model integrating clinical-psychosocial factors in predicting posttraumatic bone nonunion and bone defects. World J Psychiatry 2026; 16(9): 119455 [DOI: 10.5498/wjp.119455]

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.