AIMC Topic: Thoracic Vertebrae
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AI-based CT assessment of 3117 vertebrae reveals significant sex-specific vertebral height differences.
Scientific reports
Jul 1, 2025
Predicting vertebral height is complex due to individual factors. AI-based medical imaging analysis offers new opportunities for vertebral assessment. Thereby, these novel methods may contribute to sex-adapted nomograms and vertebral height predictio...
UANV: UNet-based attention network for thoracolumbar vertebral compression fracture angle measurement.
Scientific reports
Jun 6, 2025
Kyphosis is a prevalent spinal condition where the spine curves in the sagittal plane, resulting in spine deformities. Curvature estimation provides a powerful index to assess the deformation severity of scoliosis. In current clinical diagnosis, the ...
Machine-learning-based prediction of functional recovery in deep-pain-negative dogs after decompressive thoracolumbar hemilaminectomy for acute intervertebral disc extrusion.
Veterinary surgery : VS
Mar 25, 2025
OBJECTIVE: To develop and compare machine-learning algorithms to predict recovery of ambulation after decompressive surgery for acute intervertebral disc extrusion (IVDE).
Toward Identifying and Resolving the Challenges to the Prognostic Validation of the Classifications for Thoracolumbar Burst Fractures: A Narrative Review.
Clinical spine surgery
Mar 24, 2025
OBJECTIVE: To review the historical thoracolumbar burst fractures (TLBFs) classifications and discuss the probable gaps for their clinical validation.
Artificial intelligence for opportunistic osteoporosis screening with a Hounsfield Unit in chronic obstructive pulmonary disease patients.
Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
Feb 13, 2025
INTRODUCTION: To investigate the accuracy of an artificial intelligence (AI) prototype in determining bone mineral density (BMD) in chronic obstructive pulmonary disease (COPD) patients using chest computed tomography (CT) scans.
Waveform characteristics in thoracic paravertebral space: a prospective observational study.
F1000Research
Jan 27, 2025
BACKGROUND: With increased use of thoracic paravertebral block (TPVB) in thoracic surgery, many faced the challenge of locating the thoracic paravertebral space (TPVS) ultrasonographically. This observational study aimed to investigate the waveform c...
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 analysis of cervical balance in early-onset scoliosis post-growing rod surgery: a case-control study.
Scientific reports
Jan 15, 2025
We aimed to analyze the cervical sagittal alignment change following the growing rod treatment in early-onset scoliosis (EOS) and identify the risk factors of sagittal cervical imbalance after growing-rod surgery of machine learning. EOS patients fro...
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.
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...
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