AIMC Topic: Pressure Ulcer

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Controlled Intervention Study on Effects of an AI-Based App to Support Wound Care: First Results.

Studies in health technology and informatics May 15, 2025
The KIADEKU project combines datascience and the clinical expertise of wound experts to develop and evaluate an AI-application for incontinence-associated-dermatitis (IAD) and pressure ulcer (PU) wound care. The evaluation study is a controlled, non-...
Guideline Adherence Mobile Applications Pressure Ulcer Humans Artificial Intelligence
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Real-World Deployment of a ML Pipeline for Pressure Wounds Prediction.

Studies in health technology and informatics May 15, 2025
Hospital-acquired pressure injuries (HAPIs) are common complications that impact patient outcomes and strain healthcare resources. The Braden Scale is the standard tool for assessing HAPI risk, but it has limitations, including a high false-positive ...
Retrospective Studies Humans Decision Support Systems, Clinical Artificial Intelligence Pressure Ulcer
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Utilizing Image Processing Techniques for Wound Management and Evaluation in Clinical Practice: Establishing the Feasibility of Implementing Artificial Intelligence in Routine Wound Care.

Advances in skin & wound care May 14, 2025
OBJECTIVE: To develop a generalizable and accurate method for automatically analyzing wound images captured in clinical practice and extracting key wound characteristics such as surface area measurement.
Wounds and Injuries Pressure Ulcer Wound Healing Feasibility Studies Humans Algorithms Image Processing, Computer-Assisted Artificial Intelligence
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Investigating perioperative pressure injuries and factors influencing them with imbalanced samples using a Synthetic Minority Over-sampling Technique.

Bioscience trends May 9, 2025
This study investigates the use of machine learning (ML) models combined with a Synthetic Minority Over-sampling Technique (SMOTE) and its variants to predict perioperative pressure injuries (PIs) in an imbalanced dataset. PIs are a significant healt...
Machine Learning Algorithms Female Humans Male Middle Aged Risk Assessment Risk Factors Aged Pressure Ulcer Support Vector Machine China Decision Trees Logistic Models Perioperative Period
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Optimizing Chart Review Efficiency in Pressure Injury Evaluation Using ChatGPT.

Annals of plastic surgery Apr 1, 2025
INTRODUCTION: Wound care is an essential discipline in plastic surgery, especially as the prevalence of chronic wounds, such as pressure injuries, is increasing. The escalating volume of patient data and the numerous variables influencing wound outco...
Humans Natural Language Processing Software Pressure Ulcer
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Development of a pressure ulcer stage determination system for community healthcare providers using a vision transformer deep learning model.

Medicine Feb 14, 2025
This study reports the first steps toward establishing a computer vision system to help caregivers of bedridden patients detect pressure ulcers (PUs) early. While many previous studies have focused on using convolutional neural networks (CNNs) to ele...
Community Health Services Humans Neural Networks, Computer Deep Learning Pressure Ulcer Retrospective Studies
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Explainable Artificial Intelligence for Early Prediction of Pressure Injury Risk.

American journal of critical care : an official publication, American Association of Critical-Care Nurses Sep 1, 2024
BACKGROUND: Hospital-acquired pressure injuries (HAPIs) have a major impact on patient outcomes in intensive care units (ICUs). Effective prevention relies on early and accurate risk assessment. Traditional risk-assessment tools, such as the Braden S...
Machine Learning Algorithms Female Risk Factors Intensive Care Units Humans Artificial Intelligence Pressure Ulcer Middle Aged Risk Assessment Aged ROC Curve Male
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Evaluation of Machine Learning Algorithms for Pressure Injury Risk Assessment in a Hospital with Limited IT Resources.

Studies in health technology and informatics Aug 22, 2024
Clinical decision support systems for Nursing Process (NP-CDSSs) help resolve a critical challenge in nursing decision-making through automating the Nursing Process. NP-CDSSs are more effective when they are linked to Electronic Medical Record (EMR) ...
Pressure Ulcer Nursing Assessment Humans Risk Assessment Electronic Health Records Machine Learning Decision Support Systems, Clinical Algorithms
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Application of deep learning to pressure injury staging.

Journal of wound care May 2, 2024
OBJECTIVE: Accurate assessment of pressure injuries (PIs) is necessary for a good outcome. Junior and non-specialist nurses have less experience with PIs and lack clinical practice, and so have difficulty staging them accurately. In this work, a deep...
Deep Learning Pressure Ulcer Humans Female Neural Networks, Computer Male
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Using Artificial Intelligence for the Early Detection of Micro-Progression of Pressure Injuries in Hospitalized Patients: A Preliminary Nursing Perspective Evaluation.

Studies in health technology and informatics Jun 6, 2022
This study established a predictive model for the early detection of micro-progression of pressure injuries (PIs) from the perspective of nurses. An easy and programing-free artificial intelligence modeling tool with professional evaluation capabilit...
Hospitalization Pressure Ulcer Models, Statistical Nurses Humans Early Diagnosis Artificial Intelligence
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