AIMC Topic: Thoracic Injuries

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Exploratory cluster analysis of IL2Ra and associated biomarkers and complications after blunt chest trauma.

The journal of trauma and acute care surgery Apr 14, 2025
BACKGROUND: Rib fractures compromise approximately 40% of all fractures in the United States. Despite their prevalence, the relationship between rib fractures, solid organ injuries, and immune responses remains poorly understood. This exploratory stu...
Humans Cytokines Biomarkers Rib Fractures Adult Male Middle Aged Cluster Analysis Thoracic Injuries Wounds, Nonpenetrating Female Aged
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A risk prediction model for venous thromboembolism in hospitalized patients with thoracic trauma: a machine learning, national multicenter retrospective study.

World journal of emergency surgery : WJES Feb 13, 2025
BACKGROUND: Early treatment and prevention are the keys to reducing the mortality of VTE in patients with thoracic trauma. This study aimed to develop and validate an automatic prediction model based on machine learning for VTE risk screening in pati...
ROC Curve Predictive Value of Tests Venous Thromboembolism Machine Learning Thoracic Injuries Risk Factors Male Humans Retrospective Studies Middle Aged Female Hospitalization Risk Assessment Aged China Adult
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Diagnostic evaluation of blunt chest trauma by imaging-based application of artificial intelligence.

The American journal of emergency medicine Aug 15, 2024
Artificial intelligence (AI) is becoming increasingly integral in clinical practice, such as during imaging tasks associated with the diagnosis and evaluation of blunt chest trauma (BCT). Due to significant advances in imaging-based deep learning, re...
Artificial Intelligence Rib Fractures Thoracic Injuries Wounds, Nonpenetrating Humans Tomography, X-Ray Computed Deep Learning
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Using machine learning to predict outcomes of patients with blunt traumatic aortic injuries.

The journal of trauma and acute care surgery Mar 29, 2024
BACKGROUND: The optimal management of blunt thoracic aortic injury (BTAI) remains controversial, with experienced centers offering therapy ranging from medical management to TEVAR. We investigated the utility of a machine learning (ML) algorithm to d...
Hospital Mortality Logistic Models Registries Aorta, Thoracic Adult Male Middle Aged Endovascular Procedures Injury Severity Score Vascular System Injuries Algorithms Prognosis Thoracic Injuries Retrospective Studies Wounds, Nonpenetrating Female Risk Factors Humans Machine Learning
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Traumatic rib fracture patterns associated with bone mineral density statuses derived from CT images.

Frontiers in endocrinology Dec 12, 2023
BACKGROUND: The impact of decreased bone mineral density (BMD) on traumatic rib fractures remains unknown. We combined computed tomography (CT) and artificial intelligence (AI) to measure BMD and explore its impact on traumatic rib fractures and thei...
Wounds, Nonpenetrating Bone Density Ribs Osteoporosis Humans Tomography, X-Ray Computed Rib Fractures Artificial Intelligence Thoracic Injuries Prospective Studies Retrospective Studies
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Deep learning classification of shoulder fractures on plain radiographs of the humerus, scapula and clavicle.

PloS one Aug 30, 2023
In this study, we present a deep learning model for fracture classification on shoulder radiographs using a convolutional neural network (CNN). The primary aim was to evaluate the classification performance of the CNN for proximal humeral fractures (...
Humerus Shoulder Fractures Scapula Clavicle Humans Thoracic Injuries Deep Learning Shoulder
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The value of deep learning-based computer aided diagnostic system in improving diagnostic performance of rib fractures in acute blunt trauma.

BMC medical imaging Apr 13, 2023
BACKGROUND: To evaluate the value of a deep learning-based computer-aided diagnostic system (DL-CAD) in improving the diagnostic performance of acute rib fractures in patients with chest trauma.
Sensitivity and Specificity Humans Deep Learning Retrospective Studies Computers Wounds, Nonpenetrating Rib Fractures Thoracic Injuries Tomography, X-Ray Computed
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A pilot study of deep learning-based CT volumetry for traumatic hemothorax.

Emergency radiology Aug 16, 2022
PURPOSE: We employ nnU-Net, a state-of-the-art self-configuring deep learning-based semantic segmentation method for quantitative visualization of hemothorax (HTX) in trauma patients, and assess performance using a combination of overlap and volume-b...
Humans Thoracic Injuries Tomography, X-Ray Computed Adult Deep Learning Pilot Projects Hemothorax
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Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.

The Lancet. Digital health Jul 1, 2021
BACKGROUND: Chest x-rays are widely used in clinical practice; however, interpretation can be hindered by human error and a lack of experienced thoracic radiologists. Deep learning has the potential to improve the accuracy of chest x-ray interpretati...
Models, Biological Radiography, Thoracic Infections X-Rays Humans Mass Screening Artificial Intelligence Area Under Curve Thoracic Injuries Radiologists Adult Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Female Male Adolescent Aged Middle Aged ROC Curve Aged, 80 and over Deep Learning Thoracic Neoplasms Young Adult
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Prediction of severe chest injury using natural language processing from the electronic health record.

Injury Oct 25, 2020
INTRODUCTION: Trauma injury severity scores are currently calculated retrospectively from the electronic health record (EHR) using manual annotation by certified trauma coders. Natural language processing (NLP) of clinical documents in the EHR may en...
Electronic Health Records Humans Natural Language Processing Thoracic Injuries Unified Medical Language System Retrospective Studies
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