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http://dx.doi.org/10.1177/2192568220973984 | DOI Listing |
J Pediatr Soc North Am
August 2025
Stanford School of Medicine Department of Orthopedic Surgery, Palo Alto, CA, USA.
Background: Artificial intelligence (AI) large language models (LLMs) are becoming increasingly popular, with patients and families more likely to utilize LLM when conducting internet-based research about scoliosis. For this reason, it is vital to understand the abilities and limitations of this technology in disseminating accurate medical information. We used an expert panel to compare LLM-generated and professional society-authored answers to frequently asked questions about pediatric scoliosis.
View Article and Find Full Text PDFClin Neurol Neurosurg
October 2025
Department of Neurological Surgery, University of Chicago, Chicago, IL, USA. Electronic address:
Background And Objectives: Bone health is a critical determinant of spine surgery outcomes, yet many patients undergo procedures without adequate preoperative assessment due to limitations in current bone quality assessment methods. This study aimed to develop and validate an artificial intelligence-based algorithm that predicts Vertebral Bone Quality (VBQ) scores from routine MRI scans, enabling improved preoperative identification of patients at risk for poor surgical outcomes.
Methods: This study utilized 257 lumbar spine T1-weighted MRI scans from the SPIDER challenge dataset.
Eur Spine J
July 2025
Department of Diagnostic and Interventional Neuroradiology, School of Medicine and Health, TUM Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany.
Purpose: To investigate lumbar vertebral volumetric bone mineral density (vBMD) from ex vivo opportunistic multi-detector computed tomography (MDCT) scans using different protocols, and compare it to dedicated quantitative CT (QCT) values from the same specimens.
Methods: Cadavers from two female donors (ages 62 and 68 years) were scanned (L1-L5) using six different MDCT protocols and one dedicated QCT scan. Opportunistic vBMD was extracted using an artificial intelligence-based algorithm.
Sci Rep
July 2025
College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.
Diabetes mellitus (DM) is a serious global health concern that poses a significant threat to human life. Beyond its direct impact, diabetes substantially increases the risk of developing severe complications such as hypertension, cardiovascular disease, and musculoskeletal disorders like arthritis and osteoporosis. The field of diabetes classification has advanced significantly with the use of diverse data modalities and sophisticated tools to identify individuals or groups as diabetic.
View Article and Find Full Text PDFEur Spine J
July 2025
Department of Orthopedics, Xijing Hospital, Air Force Medical University, Xi'an, China.
Purpose: To develop an artificial intelligence (AI)-driven model for automatic Lenke classification of adolescent idiopathic scoliosis (AIS) and assess its performance.
Methods: This retrospective study utilized 860 spinal radiographs from 215 AIS patients with four views, including 161 training sets and 54 testing sets. Additionally, 1220 spinal radiographs from 610 patients with only anterior-posterior (AP) and lateral (LAT) views were collected for training.