AIMC Topic: Spinal Fractures
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Conventional and machine learning-based analysis of age, body weight and body height significance in knot position-related thyrohyoid and cervical spine fractures in suicidal hangings.
International journal of legal medicine
Feb 1, 2025
The thyrohyoid complex and cervical spine fracture distribution patterns may reflect the knot position as the force distribution by the noose to different neck regions may vary depending on it. Recently, machine learning models (MLm) were used to cla...
A deep learning pipeline for systematic and accurate vertebral fracture reporting in computed tomography.
Clinical radiology
Jan 25, 2025
AIM: Spine fractures are a frequent and relevant diagnosis, but systematic documentation is time-consuming and sometimes overlooked. A deep learning pipeline for opportunistic fracture detection in computed tomography (CT) spine images of varying fie...
Machine Learning to Detect Cervical Spine Fractures Missed by Radiologists on CT: Analysis Using Seven Award-Winning Models From the 2022 RSNA Cervical Spine Fracture AI Challenge.
AJR. American journal of roentgenology
Jan 8, 2025
Available data on radiologists' missed cervical spine fractures are based primarily on studies using human reviewers to identify errors on reevaluation; such studies do not capture the full extent of missed fractures. The purpose of this study was ...
Early prediction of functional impairment at hospital discharge in patients with osteoporotic vertebral fracture: a machine learning approach.
Scientific reports
Dec 28, 2024
Although conservative treatment is commonly used for osteoporotic vertebral fracture (OVF), some patients experience functional disability following OVF. This study aimed to develop prediction models for new-onset functional impairment following admi...
Deep learning model for automated detection of fresh and old vertebral fractures on thoracolumbar CT.
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Dec 21, 2024
PURPOSE: To develop a deep learning system for automatic segmentation of compression fracture vertebral bodies on thoracolumbar CT and differentiate between fresh and old fractures.
Artificial intelligence in risk prediction and diagnosis of vertebral fractures.
Scientific reports
Dec 19, 2024
With the increasing prevalence of vertebral fractures, accurate diagnosis and prognostication are essential. This study assesses the effectiveness of AI in diagnosing and predicting vertebral fractures through a systematic review and meta-analysis. A...
Developing predictive models for residual back pain after percutaneous vertebral augmentation treatment for osteoporotic thoracolumbar compression fractures based on machine learning technique.
Journal of orthopaedic surgery and research
Nov 28, 2024
BACKGROUND: Machine learning (ML) has been widely applied to predict the outcomes of numerous diseases. The current study aimed to develop a prognostic prediction model using machine learning algorithms and identify risk factors associated with resid...
Predictive accuracy of machine learning models for conservative treatment failure in thoracolumbar burst fractures.
BMC musculoskeletal disorders
Nov 18, 2024
BACKGROUND: The management of patients with thoracolumbar burst fractures remains a topic of debate, with conservative treatment being successful in most cases but not all. This study aimed to assess the utility of machine learning models (MLMs) in p...
Comparative efficacy of anteroposterior and lateral X-ray based deep learning in the detection of osteoporotic vertebral compression fracture.
Scientific reports
Nov 18, 2024
Magnetic resonance imaging remains the gold standard for diagnosing osteoporotic vertebral compression fractures (OVCF), but the use of X-ray imaging, particularly anteroposterior (AP) and lateral views, is prevalent due to its accessibility and cost...
Augmenting a spine CT scans dataset using VAEs, GANs, and transfer learning for improved detection of vertebral compression fractures.
Computers in biology and medicine
Nov 16, 2024
In recent years, deep learning has become a popular tool to analyze and classify medical images. However, challenges such as limited data availability, high labeling costs, and privacy concerns remain significant obstacles. As such, generative models...
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