AIMC Topic: Scoliosis

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Utilizing a comprehensive machine learning approach to identify patients at high risk for extended length of stay following spinal deformity surgery in pediatric patients with early onset scoliosis.

Spine deformity May 3, 2024
PURPOSE: Early onset scoliosis (EOS) patient diversity makes outcome prediction challenging. Machine learning offers an innovative approach to analyze patient data and predict results, including LOS in pediatric spinal deformity surgery.
Humans Machine Learning Female Risk Factors Child, Preschool Child Age of Onset Scoliosis Male Risk Assessment Length of Stay
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Correlative Assessment of Machine Learning-Based Cobb Angle Measurements and Human-Based Measurements in Adolescent Idiopathic and Congenital Scoliosis.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes Mar 27, 2024
Scoliosis is a complex spine deformity with direct functional and cosmetic impacts on the individual. The reference standard for assessing scoliosis severity is the Cobb angle which is measured on radiographs by human specialists, carrying interobse...
Male Adolescent Child Scoliosis Radiography Spine Machine Learning Retrospective Studies Female Humans
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Predicting early return to the operating room in early-onset scoliosis patients using machine learning techniques.

Spine deformity Mar 26, 2024
PURPOSE: Surgical treatment of early-onset scoliosis (EOS) is associated with high rates of complications, often requiring unplanned return to the operating room (UPROR). The aim of this study was to create and validate a machine learning model to pr...
Male Postoperative Complications Child, Preschool Child Machine Learning Retrospective Studies Female Reoperation Operating Rooms Spinal Fusion Age of Onset Scoliosis Humans
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Is there a truly significant reduction in blood loss comparing robot-assisted versus fluoroscopy-assisted pedicle screw implantation in scoliosis surgery?

Neurosurgical review Mar 21, 2024
Humans Retrospective Studies Pedicle Screws Robotics Surgery, Computer-Assisted Spinal Fusion Scoliosis Robotic Surgical Procedures Lumbar Vertebrae Fluoroscopy
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Effectiveness and safety of robot-assisted versus fluoroscopy-assisted pedicle screw implantation in scoliosis surgery: a systematic review and meta-analysis.

Neurosurgical review Mar 8, 2024
This study aimed to assess the effectiveness and safety of robot-assisted versus fluoroscopy-assisted pedicle screw implantation in scoliosis surgery. The study was registered in the PROSPERO (CRD42023471837). Two independent researchers searched Pub...
Lumbar Vertebrae Scoliosis Pedicle Screws Humans Fluoroscopy Robotics Retrospective Studies Robotic Surgical Procedures Spinal Fusion
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Deep learning algorithm for automatically measuring Cobb angle in patients with idiopathic scoliosis.

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 Feb 17, 2024
PURPOSE: The Cobb angle is a standard measurement to qualify and track the progression of scoliosis. However, the Cobb angle has high inter- and intra-observer variability. Consequently, its measurement varies with vertebrae and may even differ when ...
Female Spine Child Reproducibility of Results Humans Scoliosis Deep Learning Radiography Male Adolescent
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Deep learning prediction of curve severity from rasterstereographic back images in adolescent idiopathic scoliosis.

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 6, 2023
PURPOSE: Radiation-free systems based on dorsal surface topography can potentially represent an alternative to radiographic examination for early screening of scoliosis, based on the ability of recognizing the presence of deformity or classifying its...
Male Severity of Illness Index Deep Learning Predictive Value of Tests Radiography Adolescent Child Reproducibility of Results Young Adult Cross-Sectional Studies Humans Anthropometry Spine Scoliosis Predictive Learning Models Photogrammetry Clinical Studies as Topic
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Deep learning-based identification of spine growth potential on EOS radiographs.

European radiology Oct 18, 2023
OBJECTIVES: To develop an automatic computer-based method that can help clinicians in assessing spine growth potential based on EOS radiographs.
Spine Scoliosis Humans Algorithms Female Child Deep Learning Male Radiography Child, Preschool Infant
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Automated measurements of interscrew angles in vertebral body tethering patients with deep learning.

The spine journal : official journal of the North American Spine Society Sep 27, 2023
BACKGROUND CONTEXT: Vertebral body tethering is the most popular nonfusion treatment for adolescent idiopathic scoliosis. The effect of the tether cord on the spine can be segmentally assessed by comparing the angle between two adjacent screws (inter...
Scoliosis Reproducibility of Results Humans Vertebral Body Deep Learning Adolescent Thoracic Vertebrae Spine
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Deep Learning Model to Classify and Monitor Idiopathic Scoliosis in Adolescents Using a Single Smartphone Photograph.

JAMA network open Aug 1, 2023
IMPORTANCE: Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal disorder. Routine physical examinations by trained personnel are critical to diagnose severity and monitor curve progression in AIS. In the presence of concerning m...
Mobile Applications Monitoring, Physiologic Photography Deep Learning Humans Scoliosis Female Adolescent Male Smartphone
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