AIMC Topic: Wounds and Injuries
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[Possibilities of the utilization of trauma networks of the German Society for Trauma Surgery using digital solutions].
Unfallchirurgie (Heidelberg, Germany)
Oct 9, 2024
This paper describes the use of digital solutions to improve the care of trauma patients in Germany. The focus is on the trauma networks of the German Society for Trauma Surgery (Deutsche Gesellschaft für Unfallchirurgie, DGU). The use of digital sol...
Enhancing Performance of the National Field Triage Guidelines Using Machine Learning: Development of a Prehospital Triage Model to Predict Severe Trauma.
Journal of medical Internet research
Sep 30, 2024
BACKGROUND: Prehospital trauma triage is essential to get the right patient to the right hospital. However, the national field triage guidelines proposed by the American College of Surgeons have proven to be relatively insensitive when identifying se...
A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.
The journal of trauma and acute care surgery
Sep 27, 2024
BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly after injury. This has profound implications for resuscitation from hemorrhagic shock, as ATC is associated with increased risk for massive transfusi...
Investigation of a surrogate measure-based safety index for predicting injury crashes at signalized intersections.
Traffic injury prevention
Sep 26, 2024
OBJECTIVES: The paper develops a machine learning-based safety index for classifying traffic conflicts that can be used to estimate the frequency of signalized intersection crashes, with a focus on the more severe ones that result in fatal and severe...
Optimizing vehicle Front-End structure for e-bike rider Safety: An advanced Multi-Objective approach using injury prediction models.
Accident; analysis and prevention
Aug 29, 2024
A multi-objective optimization method based on an injury prediction model is proposed to address the increasingly prominent safety issues for e-bike riders in Chinese road traffic. This method aims to enhance the protective effect of vehicle front-en...
Mobile Apps for Wound Assessment and Monitoring: Limitations, Advancements and Opportunities.
Journal of medical systems
Aug 24, 2024
With the proliferation of wound assessment apps across various app stores and the increasing integration of artificial intelligence (AI) in healthcare apps, there is a growing need for a comprehensive evaluation system. Current apps lack sufficient e...
Machine learning models predict triage levels, massive transfusion protocol activation, and mortality in trauma utilizing patients hemodynamics on admission.
Computers in biology and medicine
Jul 16, 2024
BACKGROUND: The effective management of trauma patients necessitates efficient triaging, timely activation of Massive Blood Transfusion Protocols (MTP), and accurate prediction of in-hospital outcomes. Machine learning (ML) algorithms have emerged as...
Analyzing speed-difference impact on freeway joint injury severities of Leading-Following vehicles using statistical and data-driven models.
Accident; analysis and prevention
Jul 6, 2024
Rear-end (RE) crashes are notably prevalent and pose a substantial risk on freeways. This paper explores the correlation between speed difference among the following and leading vehicles (Δν) and RE crash risk. Three joint models, comprising both unc...
Exploring spatial heterogeneity in factors associated with injury severity in speeding-related crashes: An integrated machine learning and spatial modeling approach.
Accident; analysis and prevention
Jul 4, 2024
Speeding, a risky act of driving a vehicle at a speed exceeding the posted limit, has consistently emerged as a leading contributor to traffic fatalities. Identifying the risk factors associated with injury severity in speeding-related crashes is ess...
Prediction of mortality among severely injured trauma patients A comparison between TRISS and machine learning-based predictive models.
Injury
Jun 21, 2024
BACKGROUND: Given the huge impact of trauma on hospital systems around the world, several attempts have been made to develop predictive models for the outcomes of trauma victims. The most used, and in many studies most accurate predictive model, is t...
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