AI Medical Compendium Journal:
BMC musculoskeletal disorders

Showing 1 to 10 of 54 articles

Automatic assessment of lower limb deformities using high-resolution X-ray images.

BMC musculoskeletal disorders
BACKGROUND: Planning an osteotomy or arthroplasty surgery on a lower limb requires prior classification/identification of its deformities. The detection of skeletal landmarks and the calculation of angles required to identify the deformities are trad...

Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis.

BMC musculoskeletal disorders
BACKGROUND: Branched-chain amino acids (BCAA) metabolism is significantly associated with osteoarthritis (OA), but the specific mechanism of BCAA related genes (BCAA-RGs) in OA is still unclear. Therefore, this research intended to identify potential...

Advanced feature fusion of radiomics and deep learning for accurate detection of wrist fractures on X-ray images.

BMC musculoskeletal disorders
OBJECTIVE: The aim of this study was to develop a hybrid diagnostic framework integrating radiomic and deep features for accurate and reproducible detection and classification of wrist fractures using X-ray images.

Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models.

BMC musculoskeletal disorders
BACKGROUND: Identifying determinants of low bone mineral density (BMD) is crucial for understanding the underlying pathobiology and developing effective prevention and management strategies. Here we applied machine learning (ML) algorithms to predict...

A cross-sectional study on ChatGPT's alignment with clinical practice guidelines in musculoskeletal rehabilitation.

BMC musculoskeletal disorders
BACKGROUND: AI models like ChatGPT have the potential to support musculoskeletal rehabilitation by providing clinical insights. However, their alignment with evidence-based guidelines needs evaluation before integration into physiotherapy practice.

Torg-Pavlov ratio qualification to diagnose developmental cervical spinal stenosis based on HRViT neural network.

BMC musculoskeletal disorders
BACKGROUND: Developing computer-assisted methods to measure the Torg-Pavlov ratio (TPR), defined as the ratio of the sagittal diameter of the cervical spinal canal to the sagittal diameter of the corresponding vertebral body on lateral radiographs, c...

Machine learning models for predicting tibial intramedullary nail length.

BMC musculoskeletal disorders
BACKGROUND: Tibial intramedullary nailing (IMN) represents a standard treatment for fractures of the tibial shaft. Nevertheless, accurately predicting the appropriate nail length prior to surgery remains a challenging endeavour. Conventional techniqu...

Automated opportunistic screening for osteoporosis using deep learning-based automatic segmentation and radiomics on proximal femur images from low-dose abdominal CT.

BMC musculoskeletal disorders
RATIONALE AND OBJECTIVES: To establish an automated osteoporosis detection model based on low-dose abdominal CT (LDCT). This model combined a deep learning-based automatic segmentation of the proximal femur with a radiomics-based bone status classifi...

Comparative analysis of ChatGPT-4o mini, ChatGPT-4o and Gemini Advanced in the treatment of postmenopausal osteoporosis.

BMC musculoskeletal disorders
BACKGROUND: Osteoporosis is a sex-specific disease. Postmenopausal osteoporosis (PMOP) has been the focus of public health research worldwide. The purpose of this study is to evaluate the quality and readability of artificial intelligence large-scale...