Scalable and objective wound infection screening from clinical images using deep learning

Deep learning applied to clinical wound images provides a scalable and objective approach for wound infection screening. Such tools have the potential to support earlier detection, reduce diagnostic variability, and improve wound management and antimicrobial stewardship, particularly in public health and resource-limited settings.

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Publication Details

Journal
Frontiers in Public Health
Published
2026-02-16
DOI
https://doi.org/10.3389/fpubh.2026.1772514
Primary Topic
Pressure Ulcer Prevention and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Scalable and objective wound infection screening from clinical images using deep learning

Ziming Tan, Hao Wang, Leilei Wu, Dan Li et al.
Frontiers in Public Health
Pressure Ulcer Prevention and Management
article

Scalable and objective wound infection screening from clinical images using deep learning

Ziming Tan, Hao Wang, Leilei Wu, Dan Li, Zhiyong Huang, Jianhong Hu, Chao Wang, Yan Yang
article en

Abstract

Deep learning applied to clinical wound images provides a scalable and objective approach for wound infection screening. Such tools have the potential to support earlier detection, reduce diagnostic variability, and improve wound management and antimicrobial stewardship, particularly in public health and resource-limited settings.

Frontiers in Public HealthVol. 14
Army Medical University (CN), Sichuan University (CN), West China Second University Hospital of Sichuan University (CN), Burn Institute (US), Southwest Hospital (CN), Chengdu Second People's Hospital (CN)
Openalex Percentile: Top 53%
Pressure Ulcer Prevention and Management
DOIOpen Access PDFOpenAlex
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Scalable and objective wound infection screening from clinical images using deep learning — Ziming Tan, Hao Wang, et al. · Frontiers in Public Health (2026) | TGRS Research Map | TGRS