AIMC Topic: Wounds and Injuries

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A spatiotemporal deep learning approach for pedestrian crash risk prediction based on POI trip characteristics and pedestrian exposure intensity.

Accident; analysis and prevention Feb 8, 2024
Pedestrians represent a population of vulnerable road users who are directly exposed to complex traffic conditions, thereby increasing their risk of injury or fatality. This study first constructed a multidimensional indicator to quantify pedestrian ...
Pedestrians Accidents, Traffic Built Environment Wounds and Injuries Humans Risk Factors Deep Learning
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Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof-of-concept.

European journal of trauma and emergency surgery : official publication of the European Trauma Society Jan 24, 2024
PURPOSE: Early administration and protocolization of massive hemorrhage protocols (MHP) has been associated with decreases in mortality, multiorgan system failure, and number of blood products used. Various prediction tools have been developed for th...
Humans Machine Learning Algorithms Emergency Service, Hospital Hemorrhage Proof of Concept Study Male Injury Severity Score Middle Aged Wounds and Injuries Retrospective Studies Blood Transfusion Female Adult
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Predicting pedestrian-involved crash severity using inception-v3 deep learning model.

Accident; analysis and prevention Jan 13, 2024
This research leverages a novel deep learning model, Inception-v3, to predict pedestrian crash severity using data collected over five years (2016-2021) from Louisiana. The final dataset incorporates forty different variables related to pedestrian at...
Pedestrians Accidents, Traffic Wounds and Injuries Algorithms Deep Learning Models, Statistical Humans
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Letter to the Editor regarding 'Development of a deep learning-based tool to assist wound classification'.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS Oct 18, 2023
Humans Deep Learning Wounds and Injuries
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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...
Sweden Young Adult Triage Humans Artificial Intelligence Retrospective Studies Accidents, Traffic Injury Severity Score Wounds and Injuries
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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.
Natural Language Processing International Classification of Diseases Wounds and Injuries Humans Algorithms Electronic Health Records
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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.
Accidents, Traffic Wounds and Injuries Alabama Artificial Intelligence Female Aged Male Deep Learning Logistic Models Humans
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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...
Pakistan Wounds and Injuries Area Under Curve Humans Severity of Illness Index Bayes Theorem Machine Learning ROC Curve Accidents, Traffic Logistic Models
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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 ...
Wounds and Injuries Longitudinal Studies Self Report Humans Psychotic Disorders Neural Networks, Computer Middle Aged Psychiatric Status Rating Scales Adult Surveys and Questionnaires Cross-Sectional Studies Male Female Risk Factors Young Adult
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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...
Clinical Decision Rules Adrenal Gland Neoplasms Wounds and Injuries Incidental Findings Adult Tomography, X-Ray Computed Middle Aged Humans Sensitivity and Specificity Deep Learning Female Algorithms Male Thyroid Neoplasms Aged Retrospective Studies
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