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Clinical Validation of Object Detection Models for AI-Based Pressure Injury Stage Classification.

Sang Hyun Jang1, Chunhwa Ihm2, Jun-Woo Choi3

  • 1Department of Neurology, Daejeon Medical Center, Eulji University, Daejeon 35233, Republic of Korea.

Diagnostics (Basel, Switzerland)
|March 14, 2026
PubMed
Summary

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This summary is machine-generated.

AI models can accurately classify pressure injuries, improving consistency in care. A YOLOv7-based mobile app enhanced diagnostic accuracy and reduced assessment time for nurses.

Area of Science:

  • Medical Technology
  • Artificial Intelligence
  • Clinical Nursing

Background:

  • Clinical assessment of pressure injuries shows inconsistencies due to varying nurse experience.
  • Object detection models offer a potential solution for standardized pressure injury staging.

Purpose of the Study:

  • To develop and validate an AI-based system for accurate pressure injury stage classification.
  • To assess the clinical utility and impact on workflow efficiency of an AI diagnostic tool.

Main Methods:

  • Trained and compared five object detection models (YOLOv5x, YOLOv7, YOLOv8x, YOLOv8n, YOLOv11x, Faster R-CNN) on 1282 pressure injury images.
  • Deployed a YOLOv7-integrated mobile application for clinical testing with 10 nurses over 46 cases.

Main Results:

Keywords:
YOLOartificial intelligencedeep learningimage processingmedical applicationsobject detectionpressure injury

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  • YOLOv7 achieved superior performance (mAP@0.5: 0.97) and 93% accuracy for Stage 2 classification.
  • Clinical validation showed 87% diagnostic accuracy, high user satisfaction (4.0/5), and reduced assessment time from 4-6 min to 1 min.
  • The AI tool served as a valuable diagnostic aid and educational resource, with no critical misclassifications.

Conclusions:

  • AI-based pressure injury classification systems are practically useful in clinical settings.
  • These systems can enhance nursing competency and improve workflow efficiency.
  • The developed AI tool demonstrates potential for improving patient care through standardized assessments.