AIMC Topic: Wounds and Injuries

Clear Filters Showing 61 to 70 of 143 articles

Fully automatic wound segmentation with deep convolutional neural networks.

Scientific reports Dec 14, 2020
Acute and chronic wounds have varying etiologies and are an economic burden to healthcare systems around the world. The advanced wound care market is expected to exceed $22 billion by 2024. Wound care professionals rely heavily on images and image do...
Algorithms Image Processing, Computer-Assisted Wound Healing Wounds and Injuries Humans Neural Networks, Computer
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Do clinical and paraclinical findings have the power to predict critical conditions of injured patients after traumatic injury resuscitation? Using data mining artificial intelligence.

Chinese journal of traumatology = Zhonghua chuang shang za zhi Nov 24, 2020
PURPOSE: The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury. Early recognition of patients is an important case of such decision-making with risk of worse pr...
Data Mining Critical Illness Trauma Severity Indices Wounds and Injuries Female Artificial Intelligence Monitoring, Physiologic Humans Young Adult Middle Aged Resuscitation Triage Forecasting Adolescent Prognosis Adult Male Blood Pressure
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Using the National Trauma Data Bank (NTDB) and machine learning to predict trauma patient mortality at admission.

PloS one Nov 17, 2020
A 400-estimator gradient boosting classifier was trained to predict survival probabilities of trauma patients. The National Trauma Data Bank (NTDB) provided 799233 complete patient records (778303 survivors and 20930 deaths) each containing 32 featur...
Wounds and Injuries Glasgow Coma Scale Databases, Factual Sex Factors Humans ROC Curve Injury Severity Score Reproducibility of Results False Positive Reactions Machine Learning Risk Heart Rate Hospitalization Algorithms Probability
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Automated Quantitative Analysis of Wound Histology Using Deep-Learning Neural Networks.

The Journal of investigative dermatology Oct 26, 2020
Deep Learning Wound Healing Wounds and Injuries Humans Neural Networks, Computer
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Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network.

International journal of environmental research and public health Oct 14, 2020
A better understanding of circumstances contributing to the severity outcome of traffic crashes is an important goal of road safety studies. An in-depth crash injury severity analysis is vital for the proactive implementation of appropriate mitigatio...
Risk Factors Severity of Illness Index Saudi Arabia Logistic Models Humans Neural Networks, Computer Algorithms Accidents, Traffic Wounds and Injuries
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A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses.

Journal of orthopaedic surgery and research Aug 14, 2020
OBJECTIVE: Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resources. In this study, we compare the performance of two leading statistical and machine learning classif...
Wounds and Injuries Young Adult Adult Male Emergency Service, Hospital Patient Readmission Middle Aged Time Factors Female Risk Factors Aged Humans Machine Learning Algorithms
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Predicting Crash Injury Severity with Machine Learning Algorithm Synergized with Clustering Technique: A Promising Protocol.

International journal of environmental research and public health Jul 30, 2020
Predicting crash injury severity is a crucial constituent of reducing the consequences of traffic crashes. This study developed machine learning (ML) models to predict crash injury severity using 15 crash-related parameters. Separate ML models for ea...
Humans Machine Learning Algorithms United Kingdom Wounds and Injuries Cluster Analysis Accidents, Traffic
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Analyzing Factors Associated with Fatal Road Crashes: A Machine Learning Approach.

International journal of environmental research and public health Jun 9, 2020
Road traffic injury accounts for a substantial human and economic burden globally. Understanding risk factors contributing to fatal injuries is of paramount importance. In this study, we proposed a model that adopts a hybrid ensemble machine learning...
Humans Risk Factors Accidents, Traffic Wounds and Injuries Machine Learning Data Analysis Databases, Factual
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Forecasting deaths of road traffic injuries in China using an artificial neural network.

Traffic injury prevention Jun 5, 2020
This study was conducted to estimate road traffic deaths and to forecast short-term road traffic deaths in China using the Elman recurrent neural network (ERNN) model. An ERNN model was developed using reported police data of road traffic deaths in ...
Neural Networks, Computer Forecasting Reproducibility of Results Humans China Accidents, Traffic Wounds and Injuries
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A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo, Egypt.

International journal of injury control and safety promotion Apr 1, 2020
The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequentl...
Egypt Accidents, Traffic Quality Improvement Occupational Injuries Wounds and Injuries Trauma Severity Indices Humans Middle Aged Machine Learning Young Adult Adolescent Databases, Factual Adult Triage Female Male
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