AIMC Topic: Wounds and Injuries

Clear Filters Showing 101 to 110 of 148 articles

Rapid identification of slow healing wounds.

Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society Feb 4, 2016
Chronic nonhealing wounds have a prevalence of 2% in the United States, and cost an estimated $50 billion annually. Accurate stratification of wounds for risk of slow healing may help guide treatment and referral decisions. We have applied modern mac...
Humans Machine Learning Prognosis Retrospective Studies Disease Management Early Diagnosis Wounds and Injuries Early Medical Intervention Logistic Models Models, Theoretical Wound Healing Chronic Disease Male Aged Adolescent Female Middle Aged Aged, 80 and over Time Factors Infant, Newborn Risk Assessment Young Adult Reproducibility of Results Child, Preschool Infant Adult Child
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Telemedicine Supported Chronic Wound Tissue Prediction Using Classification Approaches.

Journal of medical systems Jan 4, 2016
Telemedicine helps to deliver health services electronically to patients with the advancement of communication systems and health informatics. Chronic wound (CW) detection and its healing rate assessment at remote distance is very much difficult due ...
Time Factors Image Processing, Computer-Assisted Fuzzy Logic Wound Healing Humans Chronic Disease Predictive Value of Tests Telemedicine Wounds and Injuries
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Automated Reconciliation of Radiology Reports and Discharge Summaries.

AMIA ... Annual Symposium proceedings. AMIA Symposium Nov 5, 2015
We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g...
Software Diagnostic Errors Support Vector Machine Natural Language Processing Wounds and Injuries Emergency Service, Hospital Humans Radiology Machine Learning Extremities Radiology Information Systems Patient Discharge Summaries
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Prediction of feature genes in trauma patients with the TNF rs1800629 A allele using support vector machine.

Computers in biology and medicine Jun 9, 2015
BACKGROUND: Tumor necrosis factor (TNF)-α variant is closely linked to sepsis syndrome and mortality after severe trauma. We aimed to identify feature genes associated with the TNF rs1800629 A allele in trauma patients and help to direct them toward ...
Wounds and Injuries Ribosomal Proteins Humans Tumor Necrosis Factor-alpha Gene Expression Profiling Support Vector Machine Alleles Heme Oxygenase-1
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Injury narrative text classification using factorization model.

BMC medical informatics and decision making May 20, 2015
Narrative text is a useful way of identifying injury circumstances from the routine emergency department data collections. Automatically classifying narratives based on machine learning techniques is a promising technique, which can consequently redu...
Humans Data Mining Machine Learning Medical Informatics Narration Medical Records Wounds and Injuries
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Variable importance and prediction methods for longitudinal problems with missing variables.

PloS one Mar 27, 2015
We present prediction and variable importance (VIM) methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patie...
Trauma Centers Humans Machine Learning Longitudinal Studies Algorithms Predictive Value of Tests Prognosis Evidence-Based Medicine Wounds and Injuries
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Machine learning approaches to analysing textual injury surveillance data: a systematic review.

Accident; analysis and prevention Mar 19, 2015
OBJECTIVE: To synthesise recent research on the use of machine learning approaches to mining textual injury surveillance data.
Statistics as Topic Wounds and Injuries Child Models, Theoretical Population Surveillance Data Mining Infant Adolescent Child, Preschool Female Infant, Newborn Aged Aged, 80 and over Young Adult Adult Male Humans Middle Aged Machine Learning
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Bridging a translational gap: using machine learning to improve the prediction of PTSD.

BMC psychiatry Mar 16, 2015
BACKGROUND: Predicting Posttraumatic Stress Disorder (PTSD) is a pre-requisite for targeted prevention. Current research has identified group-level risk-indicators, many of which (e.g., head trauma, receiving opiates) concern but a subset of survivor...
Algorithms Prognosis Female Risk Factors Adult Male Middle Aged Risk Assessment Humans Artificial Intelligence Adaptation, Psychological Stress Disorders, Post-Traumatic Wounds and Injuries ROC Curve Translational Research, Biomedical Early Diagnosis
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Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

International journal of injury control and safety promotion Dec 4, 2013
Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial...
Accidents, Traffic Wounds and Injuries Algorithms Forecasting Models, Statistical Humans Neural Networks, Computer
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Context-dependent effects of built environment factors on pedestrian-injury severities with imbalanced and high dimensional crash data.

Accident; analysis and prevention Aug 1, 2025
Built environment is an important component that influences pedestrian injury severities in pedestrian-vehicle crashes. Previous studies indicated that the effects of various built environment factors on pedestrian injury severities are heterogeneous...
Accidents, Traffic North Carolina Built Environment Wounds and Injuries Humans Machine Learning Environment Design Pedestrians
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