AIMC Topic: Trauma Severity Indices

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Robot-assisted upper extremity rehabilitation for cervical spinal cord injuries: a systematic scoping review.

Disability and rehabilitation. Assistive technology Jan 15, 2018
UNLABELLED: Abstact Purpose: To provide an overview of the feasibility and outcomes of robotic-assisted upper extremity training for individuals with cervical spinal cord injury (SCI), and to identify gaps in current research and articulate future re...
Upper Extremity Physical Therapy Modalities Trauma Severity Indices Robotics Sex Factors Cervical Cord Spinal Cord Injuries Humans Age Factors Recovery of Function
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Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

International journal of injury control and safety promotion Sep 8, 2016
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...
Cluster Analysis Area Under Curve Accidents, Traffic United Arab Emirates Wounds and Injuries Trauma Severity Indices Male Forecasting Middle Aged Female Humans Adolescent Young Adult Neural Networks, Computer ROC Curve Adult
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Investigating driver injury severity patterns in rollover crashes using support vector machine models.

Accident; analysis and prevention Mar 1, 2016
Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector ...
Humans Support Vector Machine Male Female Trauma Severity Indices Middle Aged Environment Design Aged Accidents, Traffic Adolescent New Mexico Logistic Models Automobile Driving Seat Belts Young Adult Adult
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A novel mathematical model to predict prognosis of burnt patients based on logistic regression and support vector machine.

Burns : journal of the International Society for Burn Injuries Jan 13, 2016
OBJECTIVE: To develop a mathematical model of predicting mortality based on the admission characteristics of 6220 burn cases.
Support Vector Machine Prognosis Principal Component Analysis Infant, Newborn Smoke Inhalation Injury Multivariate Analysis Humans Child Aged Burns Trauma Severity Indices Body Surface Area ROC Curve Young Adult Shock Middle Aged Logistic Models Adult Infant Models, Theoretical Adolescent Child, Preschool
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[Comparison of ICD 10 and AIS with the Development of a Method for Automated Conversion].

Zeitschrift fur Orthopadie und Unfallchirurgie Oct 15, 2015
BACKGROUND: Most of the current scores and outcome prediction calculations in traumatology are based on the Abbreviated Injury Scale (AIS). However, this is not routinely used for documentation and coding of injuries in many countries, including Germ...
Algorithms Natural Language Processing Information Storage and Retrieval Pattern Recognition, Automated International Classification of Diseases Forms and Records Control Trauma Severity Indices
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Features identification for automatic burn classification.

Burns : journal of the International Society for Burn Injuries Jul 15, 2015
PURPOSE: In this paper an automatic system to diagnose burn depths based on colour digital photographs is presented.
Automation Photography Trauma Severity Indices Burn Units Algorithms Humans Diagnosis, Computer-Assisted Databases, Factual Support Vector Machine Reproducibility of Results Skin Sensitivity and Specificity Burns
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Permutation entropy analysis of vital signs data for outcome prediction of patients with severe traumatic brain injury.

Computers in biology and medicine Nov 15, 2014
Permutation entropy is computationally efficient, robust to outliers, and effective to measure complexity of time series. We used this technique to quantify the complexity of continuous vital signs recorded from patients with traumatic brain injury (...
Predictive Value of Tests Humans Vital Signs Artificial Intelligence Trauma Severity Indices Databases, Factual Brain Injuries
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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...
Natural Language Processing Registries Injury Severity Score Wounds and Injuries Trauma Severity Indices Humans Machine Learning Electronic Health Records
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Clinical decision support for severe trauma patients: Machine learning based definition of a bundle of care for hemorrhagic shock and traumatic brain injury.

The journal of trauma and acute care surgery Jan 1, 2022
BACKGROUND: Deviation from guidelines is frequent in emergency situations, and this may lead to increased mortality. Probably because of time constraints, 55% is the greatest reported guidelines compliance rate in severe trauma patients. This study a...
Quality Improvement Practice Guidelines as Topic France Shock, Hemorrhagic Emergency Medical Services Registries Patient Care Bundles Critical Care Trauma Severity Indices Humans Machine Learning Female Adult Decision Support Systems, Clinical Guideline Adherence Brain Injuries, Traumatic Male Hospital Mortality
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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 Aged, 80 and over Adult Male Middle Aged Risk Assessment Prospective Studies Clinical Decision-Making Female Aged Blood Coagulation Disorders Wounds and Injuries London Trauma Severity Indices Adolescent Predictive Value of Tests Bayes Theorem Supervised Machine Learning
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