AIMC Topic: Wounds and Injuries

Clear Filters Showing 51 to 60 of 143 articles

On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry.

BMC medical informatics and decision making Oct 9, 2023
BACKGROUND: Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient's condition and deciding on transport destination. Data-driven On Scene Injur...
Humans Artificial Intelligence Triage Accidents, Traffic Injury Severity Score Wounds and Injuries Retrospective Studies Sweden Young Adult
View on PubMed DOI

TraumaICD Bidirectional Encoder Representation From Transformers: A Natural Language Processing Algorithm to Extract Injury International Classification of Diseases, 10th Edition Diagnosis Code From Free Text.

Annals of surgery Sep 27, 2023
OBJECTIVE: To develop and validate TraumaICDBERT, a natural language processing algorithm to predict injury International Classification of Diseases, 10th edition (ICD-10) diagnosis codes from trauma tertiary survey notes.
International Classification of Diseases Humans Wounds and Injuries Algorithms Electronic Health Records Natural Language Processing
View on PubMed DOI

Older driver at-fault crashes at unsignalized intersections in Alabama: Injury severity analysis with supporting evidence from a deep learning based approach.

Journal of safety research Apr 27, 2023
INTRODUCTION: The research described in this paper explored the factors contributing to the injury severity resulting from the male and female older driver (65 years and older) at-fault crashes at unsignalized intersections in Alabama.
Male Deep Learning Logistic Models Alabama Accidents, Traffic Wounds and Injuries Artificial Intelligence Female Aged Humans
View on PubMed DOI

Hybrid feature selection-based machine learning Classification system for the prediction of injury severity in single and multiple-vehicle accidents.

PloS one Feb 2, 2022
To undertake a reliable analysis of injury severity in road traffic accidents, a complete understanding of important attributes is essential. As a result of the shift from traditional statistical parametric procedures to computer-aided methods, machi...
Humans Logistic Models Area Under Curve Bayes Theorem Accidents, Traffic Machine Learning Severity of Illness Index ROC Curve Pakistan Wounds and Injuries
View on PubMed DOI

Network analysis of trauma in patients with early-stage psychosis.

Scientific reports Nov 23, 2021
Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are common in psychosis. The present study aimed to perform a network analysis of interactions between ...
Psychotic Disorders Wounds and Injuries Surveys and Questionnaires Longitudinal Studies Self Report Risk Factors Young Adult Adult Middle Aged Psychiatric Status Rating Scales Cross-Sectional Studies Male Humans Neural Networks, Computer Female
View on PubMed DOI

Automatic Detection of Thyroid and Adrenal Incidentals Using Radiology Reports and Deep Learning.

The Journal of surgical research May 18, 2021
BACKGROUND: Computed tomography (CT) is commonly performed when evaluating trauma patients with up to 55% showing incidental findings. Current workflows to identify and inform patients are time-consuming and prone to error. Our objective was to autom...
Humans Algorithms Retrospective Studies Aged Adult Tomography, X-Ray Computed Female Incidental Findings Deep Learning Clinical Decision Rules Thyroid Neoplasms Sensitivity and Specificity Adrenal Gland Neoplasms Male Wounds and Injuries Middle Aged
View on PubMed DOI

Predicting venous thromboembolism in hospitalized trauma patients: a combination of the Caprini score and data-driven machine learning model.

BMC emergency medicine May 10, 2021
BACKGROUND: Venous thromboembolism (VTE) is a common complication of hospitalized trauma patients and has an adverse impact on patient outcomes. However, there is still a lack of appropriate tools for effectively predicting VTE for trauma patients. W...
Risk Assessment Venous Thromboembolism Wounds and Injuries Humans Machine Learning Risk Factors Hospitalization Retrospective Studies
View on PubMed DOI

Open data and injuries in urban areas-A spatial analytical framework of Toronto using machine learning and spatial regressions.

PloS one Mar 11, 2021
Injuries have become devastating and often under-recognized public health concerns. In Canada, injuries are the leading cause of potential years of life lost before the age of 65. The geographical patterns of injury, however, are evident both over sp...
Wounds and Injuries Cities Humans Canada Urban Health Machine Learning Databases, Factual
View on PubMed DOI

A scalable physician-level deep learning algorithm detects universal trauma on pelvic radiographs.

Nature communications Feb 16, 2021
Pelvic radiograph (PXR) is essential for detecting proximal femur and pelvis injuries in trauma patients, which is also the key component for trauma survey. None of the currently available algorithms can accurately detect all kinds of trauma-related ...
Pelvis Hip Fractures Wounds and Injuries Middle Aged Female Deep Learning ROC Curve Aged Adult Humans Male Algorithms Physicians
View on PubMed DOI

Identifying intentional injuries among children and adolescents based on Machine Learning.

PloS one Jan 20, 2021
BACKGROUND: Compared to other studies, the injury monitoring of Chinese children and adolescents has captured a low level of intentional injuries on account of self-harm/suicide and violent attacks. Intentional injuries in children and adolescents ha...
Self-Injurious Behavior Violence Wounds and Injuries Child, Preschool Humans Adolescent Child Machine Learning Intention Female Suicide Male
View on PubMed DOI
Popular Topics
Recent Journals