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Open-source artificial intelligence models (OSAIM) find free applications in various industries, including information technology and medicine. Their clinical potential, especially in supporting diagnosis and therapy, is the subject of increasingly intensive research. Due to the growing interest in artificial intelligence (AI) for diagnostic purposes, we conducted a study evaluating the capabilities of AI models, including ChatGPT and Microsoft Bing, in the diagnosis of single-curve scoliosis based on posturographic radiological images. Two independent neurosurgeons assessed the degree of spinal deformation, selecting 23 cases of severe single-curve scoliosis. Each posturographic image was separately implemented onto each of the mentioned platforms using a set of formulated questions, starting from 'What do you see in the image?' and ending with a request to determine the Cobb angle. In the responses, we focused on how these AI models identify and interpret spinal deformations and how accurately they recognize the direction and type of scoliosis as well as vertebral rotation. The Intraclass Correlation Coefficient (ICC) with a 'two-way' model was used to assess the consistency of Cobb angle measurements, and its confidence intervals were determined using the F test. Differences in Cobb angle measurements between human assessments and the AI ChatGPT model were analyzed using metrics such as RMSEA, MSE, MPE, MAE, RMSLE, and MAPE, allowing for a comprehensive assessment of AI model performance from various statistical perspectives. The ChatGPT model achieved 100% effectiveness in detecting scoliosis in X-ray images, while the Bing model did not detect any scoliosis. However, ChatGPT had limited effectiveness (43.5%) in assessing Cobb angles, showing significant inaccuracy and discrepancy compared to human assessments. This model also had limited accuracy in determining the direction of spinal curvature, classifying the type of scoliosis, and detecting vertebral rotation. Overall, although ChatGPT demonstrated potential in detecting scoliosis, its abilities in assessing Cobb angles and other parameters were limited and inconsistent with expert assessments. These results underscore the need for comprehensive improvement of AI algorithms, including broader training with diverse X-ray images and advanced image processing techniques, before they can be considered as auxiliary in diagnosing scoliosis by specialists.
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http://dx.doi.org/10.3390/diagnostics14070773 | DOI Listing |
JB JS Open Access
September 2025
Department of Orthopaedics and Traumatology, The University of Hong Kong, Pokfulam, Hong Kong SAR, People's Republic of China.
Background: Cervical vertebral maturation (CVM) is a skeletal maturity method that can be assessed routinely on whole spine radiographs to minimize radiation exposure. Originally used in orthodontics, its role in staging adolescent growth spurt and curve progression in adolescent idiopathic scoliosis (AIS) remains unclear. The aim of this study was to investigate growth rates across CVM stages, its cutoff for indicating peak growth (PG) versus growth cessation (GC), and its relationship with coronal curve progression.
View Article and Find Full Text PDFJ Am Acad Orthop Surg
August 2025
From the Department of Orthopedic Surgery (Daher, Aoun, Sebaaly), Hotel Dieu de France Hospital, Beirut, LEBANON, the Department of Orthopedic Surgery (Daher, Diebo, Daniels), Brown University, Providence, RI, the Department of Orthopedic Surgery (Daher, Cottrill, Passias), Duke University, Durham,
Background: Surgical management of thoracolumbar fractures in patients with ankylosing spinal disorders such as ankylosing spondylitis (AS) and diffuse idiopathic skeletal hyperostosis remains debated. Although several studies have compared minimally invasive surgery to open fixation of thoracolumbar fractures in this patient population, a meta-analysis compiling the literature on this topic is lacking.
Methods: Following the PRISMA guidelines, PubMed, Cochrane, and Google Scholar (pages 1 to 20) were accessed and explored until October 2024.
Cureus
August 2025
Department of Neurosurgery, Virginia Commonwealth University, Richmond, USA.
Background Anterior cervical discectomy and fusion (ACDF) is a common surgical procedure that patients undergo for cervical disc herniations and degenerative disc disease, aimed at relieving radicular symptoms and restoring cervical alignment. The impact of preoperative kyphotic cervical imbalance versus preoperative lordosis on postoperative radiographic outcomes in ACDF patients is unclear. The purpose of this study is to examine how preoperative cervical sagittal balance can influence quantified postoperative cervical sagittal balance.
View Article and Find Full Text PDFPaediatr Child Health
August 2025
Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Objectives: Cobb angle is a standard method for quantification of scoliosis in adolescent idiopathic scoliosis to guide treatment decisions. Precise and timely curve detection can ensure early referrals, amenable for bracing. Radiology reports serve as a guiding tool for family physicians to expedite specialist referrals.
View Article and Find Full Text PDFEur Spine J
September 2025
Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Purpose: This study aims to address the limitations of radiographic imaging and single-task learning models in adolescent idiopathic scoliosis assessment by developing a noninvasive, radiation-free diagnostic framework.
Methods: A multi-task deep learning model was trained using structured back surface data acquired via fringe projection three-dimensional imaging. The model was designed to simultaneously predict the Cobb angle, curve type (thoracic, lumbar, mixed, none), and curve direction (left, right, none) by learning shared morphological features.