AIMC Topic: Wounds and Injuries

Clear Filters Showing 121 to 130 of 148 articles

Automatic Classification of Wound Images Showing Healing Complications: Towards an Optimised Approach for Detecting Maceration.

Studies in health technology and informatics Aug 30, 2024
This study aims to advance the field of digital wound care by developing and evaluating convolutional neural network (CNN) architectures for the automatic classification of maceration, a significant wound healing complication, in 458 annotated wound ...
Wounds and Injuries Neural Networks, Computer Wound Healing Humans Image Interpretation, Computer-Assisted
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Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery.

Studies in health technology and informatics Aug 22, 2024
AIM: Feasibility and reliability evaluation of 5G internet networks (5G IN) upon Artificial Intelligence (AI)/Machine Learning (ML), of telemonitoring and mobile ultrasound (m u/s) in an ambulance car (AC)- integrated in the pre-hospital setting (PS)...
Humans Artificial Intelligence Machine Learning Internet Feasibility Studies Telemedicine Wounds and Injuries Reproducibility of Results Ultrasonography Emergency Medical Services
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Automated stratification of trauma injury severity across multiple body regions using multi-modal, multi-class machine learning models.

Journal of the American Medical Informatics Association : JAMIA May 20, 2024
OBJECTIVE: The timely stratification of trauma injury severity can enhance the quality of trauma care but it requires intense manual annotation from certified trauma coders. The objective of this study is to develop machine learning models for the st...
Electronic Health Records Humans Natural Language Processing Trauma Severity Indices Machine Learning Registries Injury Severity Score Wounds and Injuries
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[Application and prospect of machine learning in orthopaedic trauma].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery Dec 15, 2023
OBJECTIVE: To review the current applications of machine learning in orthopaedic trauma and anticipate its future role in clinical practice.
Humans Artificial Intelligence Machine Learning Orthopedics Algorithms Biomedical Research Wounds and Injuries
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Risk profiling in the prevention and treatment of chronic wounds using artificial intelligence.

International wound journal Oct 1, 2022
Wounds and Injuries Humans Artificial Intelligence Risk Assessment
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The derivation of an International Classification of Diseases, Tenth Revision-based trauma-related mortality model using machine learning.

The journal of trauma and acute care surgery Mar 1, 2022
BACKGROUND: Existing mortality prediction models have attempted to quantify injury burden following trauma-related admissions with the most notable being the Injury Severity Score (ISS). Although easy to calculate, it requires additional administrati...
Survival Analysis Datasets as Topic International Classification of Diseases Wounds and Injuries Humans Machine Learning Decision Trees
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Electronic health record machine learning model predicts trauma inpatient mortality in real time: A validation study.

The journal of trauma and acute care surgery Jan 1, 2022
INTRODUCTION: Patient outcome prediction models are underused in clinical practice because of lack of integration with real-time patient data. The electronic health record (EHR) has the ability to use machine learning (ML) to develop predictive model...
Hospital Mortality United States Predictive Value of Tests Injury Severity Score Wounds and Injuries Registries Critical Care Male Humans Middle Aged Machine Learning Risk Assessment Prognosis Electronic Health Records Female
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Predicting outcomes after trauma: Prognostic model development based on admission features through machine learning.

Medicine Dec 10, 2021
In an overcrowded emergency department (ED), trauma surgeons and emergency physicians need an accurate prognostic predictor for critical decision-making involving patients with severe trauma. We aimed to develope a machine learning-based early progno...
Glasgow Coma Scale Injury Severity Score Patient Admission Wounds and Injuries Middle Aged Humans Taiwan Aged Machine Learning Prognosis Emergency Medical Services Adult Aged, 80 and over Retrospective Studies Male Female
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Early Identification of Trauma-induced Coagulopathy: Development and Validation of a Multivariable Risk Prediction Model.

Annals of surgery Dec 1, 2021
OBJECTIVE: The aim of this study was to develop and validate a risk prediction tool for trauma-induced coagulopathy (TIC), to support early therapeutic decision-making.
Humans Prospective Studies Aged Aged, 80 and over Clinical Decision-Making Female Supervised Machine Learning Risk Assessment Blood Coagulation Disorders Adult Adolescent Wounds and Injuries London Male Predictive Value of Tests Trauma Severity Indices Middle Aged Bayes Theorem
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Enhancing Military Burn- and Trauma-Related Acute Kidney Injury Prediction Through an Automated Machine Learning Platform and Point-of-Care Testing.

Archives of pathology & laboratory medicine Mar 1, 2021
CONTEXT.—: Delayed recognition of acute kidney injury (AKI) results in poor outcomes in military and civilian burn-trauma care. Poor predictive ability of urine output (UOP) and creatinine contribute to the delayed recognition of AKI.
Military Personnel Wounds and Injuries Lipocalin-2 Burns Creatinine Aged Aged, 80 and over Adult Biomarkers Predictive Value of Tests Humans Acute Kidney Injury Male Point-of-Care Testing Machine Learning Middle Aged Female Algorithms
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