AIMC Topic: Trauma Severity Indices
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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...
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...
Model for Predicting In-Hospital Mortality of Physical Trauma Patients Using Artificial Intelligence Techniques: Nationwide Population-Based Study in Korea.
Journal of medical Internet research
Dec 13, 2022
BACKGROUND: Physical trauma-related mortality places a heavy burden on society. Estimating the mortality risk in physical trauma patients is crucial to enhance treatment efficiency and reduce this burden. The most popular and accurate model is the In...
Relationship between Machine-Learning Image Classification of T-Weighted Intramedullary Hypointensity on 3 Tesla Magnetic Resonance Imaging and Clinical Outcome in Dogs with Severe Spinal Cord Injury.
Journal of neurotrauma
Dec 4, 2020
Early prognostic information in cases of severe spinal cord injury can aid treatment planning and stratification for clinical trials. Analysis of intraparenchymal signal change on magnetic resonance imaging has been suggested to inform outcome predic...
Do clinical and paraclinical findings have the power to predict critical conditions of injured patients after traumatic injury resuscitation? Using data mining artificial intelligence.
Chinese journal of traumatology = Zhonghua chuang shang za zhi
Nov 24, 2020
PURPOSE: The triage and initial care of injured patients and a subsequent right level of care is paramount for an overall outcome after traumatic injury. Early recognition of patients is an important case of such decision-making with risk of worse pr...
BPBSAM: Body part-specific burn severity assessment model.
Burns : journal of the International Society for Burn Injuries
May 4, 2020
BACKGROUND AND OBJECTIVE: Burns are a serious health problem leading to several thousand deaths annually, and despite the growth of science and technology, automated burns diagnosis still remains a major challenge. Researchers have been exploring vis...
A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo, Egypt.
International journal of injury control and safety promotion
Apr 1, 2020
The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequentl...
The trauma severity model: An ensemble machine learning approach to risk prediction.
Computers in biology and medicine
Mar 6, 2019
Statistical theory indicates that a flexible model can attain a lower generalization error than an inflexible model, provided that the setting is appropriate. This is highly relevant for mortality risk prediction with trauma patients, as researchers ...
Using Machine Learning to Identify Change in Surgical Decision Making in Current Use of Damage Control Laparotomy.
Journal of the American College of Surgeons
Jan 9, 2019
BACKGROUND: In an earlier study, we reported the successful reduction in the use of damage control laparotomy (DCL); however, no change in the relative frequencies of specific indications was observed. In this study, we aimed to use machine learning ...
Deep learning algorithms for detection of critical findings in head CT scans: a retrospective study.
Lancet (London, England)
Oct 11, 2018
BACKGROUND: Non-contrast head CT scan is the current standard for initial imaging of patients with head trauma or stroke symptoms. We aimed to develop and validate a set of deep learning algorithms for automated detection of the following key finding...
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