AIMC Topic: Trauma Centers

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Predicting opportunities for improvement in trauma care using machine learning: a retrospective registry-based study at a major trauma centre.

BMJ open Jun 6, 2025
OBJECTIVE: To develop models to predict opportunities for improvement in trauma care and compare the performance of these models to the currently used audit filters.
Female Adult Male Middle Aged Humans Quality Improvement Machine Learning Retrospective Studies Injury Severity Score Wounds and Injuries Trauma Centers ROC Curve Logistic Models Registries
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An open source convolutional neural network to detect and localize distal radius fractures on plain radiographs.

European journal of trauma and emergency surgery : official publication of the European Trauma Society Jan 17, 2025
PURPOSE: Distal radius fractures (DRFs) are often initially assessed by junior doctors under time constraints, with limited supervision, risking significant consequences if missed. Convolutional Neural Networks (CNNs) can aid in diagnosing fractures....
Humans Neural Networks, Computer Middle Aged Convolutional Neural Networks Radiography Radius Fractures Trauma Centers Wrist Injuries Wrist Fractures Aged Aged, 80 and over Adult Male Algorithms Retrospective Studies Female
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Forecasting Pediatric Trauma Volumes: Insights From a Retrospective Study Using Machine Learning.

The Journal of surgical research Dec 31, 2024
INTRODUCTION: Rising pediatric firearm-related fatalities in the United States strain Trauma Centers. Predicting trauma volume could improve resource management and preparedness, particularly if daily forecasts are achievable. The aim of the study is...
Male Infant Adolescent Child, Preschool Forecasting Retrospective Studies Female Trauma Centers Wounds, Gunshot Child United States Wounds and Injuries Humans Machine Learning
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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...
International Normalized Ratio Hemorrhage Blood Coagulation Disorders Wounds and Injuries Trauma Centers Male Middle Aged Risk Assessment Blood Transfusion Machine Learning Humans Female Adult
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Establishing an open and robotic pancreatic surgery program in a level 1 trauma center community teaching hospital and comparing its outcomes to high-volume academic center outcomes: a retrospective review.

BMC surgery Dec 6, 2022
BACKGROUND: The debate of whether to centralize hepato-pancreato-biliary surgery has been ongoing. The principal objective was to compare outcomes of a community pancreatic surgical program with those of high-volume academic centers.
Humans Robotics Trauma Centers Hospitals, Teaching
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Retrospective analysis and prospective validation of an AI-based software for intracranial haemorrhage detection at a high-volume trauma centre.

Scientific reports Nov 18, 2022
Rapid detection of intracranial haemorrhage (ICH) is crucial for assessing patients with neurological symptoms. Prioritising these urgent scans for reporting presents a challenge for radiologists. Artificial intelligence (AI) offers a solution to ena...
Intracranial Hemorrhages Trauma Centers Artificial Intelligence Software Retrospective Studies Humans Australia
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Decision-making in pediatric blunt solid organ injury: A deep learning approach to predict massive transfusion, need for operative management, and mortality risk.

Journal of pediatric surgery Oct 24, 2020
BACKGROUND: The principal triggers for intervention in the setting of pediatric blunt solid organ injury (BSOI) are declining hemoglobin values and hemodynamic instability. The clinical management of BSOI is, however, complex. We therefore hypothesiz...
Humans Retrospective Studies Wounds, Nonpenetrating Deep Learning Child Spleen Injury Severity Score Trauma Centers
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Artificial intelligence in trauma systems.

Surgery Sep 10, 2020
Local trauma care and regional trauma systems are data-rich environments that are amenable to machine learning, artificial intelligence, and big-data analysis mechanisms to improve timely access to care, to measure outcomes, and to improve quality of...
Regional Health Planning Outcome Assessment, Health Care Decision Making, Organizational Trauma Centers Resource Allocation Big Data United States Health Services Accessibility Humans Machine Learning Forecasting
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Using Machine Learning to Make Predictions in Patients Who Fall.

The Journal of surgical research Aug 18, 2020
BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothesize that a machine learning algorithm can more accurately predict mortality after a fall compared with a standard logistic regression (LR) model base...
Length of Stay Accidental Falls ROC Curve Decision Trees Machine Learning Adult Glasgow Coma Scale Algorithms Male Patient Discharge Retrospective Studies Middle Aged Intensive Care Units Humans Injury Severity Score Female Trauma Centers Aged Aged, 80 and over
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Exploring the Role of Artificial Intelligence in an Emergency and Trauma Radiology Department.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Apr 20, 2020
Emergency and trauma radiologists, emergency department's physicians and nurses, researchers, departmental leaders, and health policymakers have attempted to discover efficient approaches to enhance the provision of quality patient care. There are in...
Radiology Humans Artificial Intelligence Image Interpretation, Computer-Assisted Trauma Centers Emergency Service, Hospital
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