AIMC Topic: Wounds and Injuries

Clear Filters Showing 61 to 70 of 160 articles

[Orthopedics and trauma surgery in the digital age].

Orthopadie (Heidelberg, Germany)
BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedicine, digital health applications, electronic patient records and artificial intelligence play a central role in this. These technologies have the pot...

Potential of artificial intelligence in injury prevention research and practice.

Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
There is increasing interest and use of artificial Intelligence algorithms and methods in biomedical research and practice, particularly as the technology has made significant advances in the past decade and become more accessible to more disciplines...

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

Accident; analysis and prevention
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 ...

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
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...

Predicting pedestrian-involved crash severity using inception-v3 deep learning model.

Accident; analysis and prevention
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...

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

BMC medical informatics and decision making
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...

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
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.

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
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.

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

PloS one
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...