AIMC Topic: Scoliosis
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Accuracy of computer-assisted pedicle screw placement for adolescent idiopathic scoliosis: a comparison between robotics and navigation.
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 26, 2022
PURPOSE: To compare the accuracy of pedicle screw placement in adolescent idiopathic scoliosis (AIS) between robotics and navigation and clarify the factors that cause screw deviation when robotics is used.
Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.
World neurosurgery
Aug 30, 2022
BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the analysis of language and text. Although NLP has been applied to various forms of clinical text, the applications and utility of NLP in spine surgery ...
Pedicle Screw Placement in Adolescent Idiopathic Scoliosis: A Comparison between Robotics Coupled with Navigation versus the Freehand Technique.
Sensors (Basel, Switzerland)
Jul 12, 2022
(1) Background: Robotics coupled with navigation (RAN) is a modern surgical platform shown to increase screw placement accuracy during pediatric scoliosis surgery. Our institution uses a technique which combines the RAN platform for apical pedicle sc...
Automatic Cobb angle measurement method based on vertebra segmentation by deep learning.
Medical & biological engineering & computing
Jun 9, 2022
The accuracy of the Cobb measurement is essential for the diagnosis and treatment of scoliosis. Manual measurement is however influenced by the observer variability hence affecting progression evaluation. In this paper, we propose a fully automatic C...
A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation.
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
May 21, 2022
PURPOSE: To propose a fully automated deep learning (DL) framework for the vertebral morphometry and Cobb angle measurement from three-dimensional (3D) computed tomography (CT) images of the spine, and validate the proposed framework on an external d...
Using deep transfer learning to detect scoliosis and spondylolisthesis from x-ray images.
PloS one
May 2, 2022
Recent years have witnessed wider prevalence of vertebral column pathologies due to lifestyle changes, sedentary behaviors, or injuries. Spondylolisthesis and scoliosis are two of the most common ailments with an incidence of 5% and 3% in the United ...
PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.
American journal of human genetics
Jan 20, 2022
In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapi...
Comparison of manual versus automated measurement of Cobb angle in idiopathic scoliosis based on a deep learning keypoint detection technology.
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
Oct 30, 2021
PURPOSE: The present study compared manual and automated measurement of Cobb angle in idiopathic scoliosis based on deep learning keypoint detection technology.
An algorithm for using deep learning convolutional neural networks with three dimensional depth sensor imaging in scoliosis detection.
The spine journal : official journal of the North American Spine Society
Feb 1, 2021
BACKGROUND CONTEXT: Timely intervention in growing individuals, such as brace treatment, relies on early detection of adolescent idiopathic scoliosis (AIS). To this end, several screening methods have been implemented. However, these methods have lim...
Artificial Intelligence Models Predict Operative Versus Nonoperative Management of Patients with Adult Spinal Deformity with 86% Accuracy.
World neurosurgery
May 17, 2020
OBJECTIVE: Patients with ASD show complex and highly variable disease. The decision to manage patients operatively is largely subjective and varies based on surgeon training and experience. We sought to develop models capable of accurately discrimina...
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