AIMC Topic: Bone Density
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The Effectiveness of Artificial Intelligence-based Pedicle Screw Trajectory Planning in Patients With Different Levels of Bone Mineral Density.
Clinical spine surgery
Sep 3, 2024
STUDY DESIGN: Retrospective cohort study.
Estimating lumbar bone mineral density from conventional MRI and radiographs with deep learning in spine patients.
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
Aug 30, 2024
PURPOSE: This study aimed to develop machine learning methods to estimate bone mineral density and detect osteopenia/osteoporosis from conventional lumbar MRI (T1-weighted and T2-weighted images) and planar radiography in combination with clinical da...
Machine learning models can define clinically relevant bone density subgroups based on patient-specific calibrated computed tomography scans in patients undergoing reverse shoulder arthroplasty.
Journal of shoulder and elbow surgery
Aug 16, 2024
BACKGROUND: Reduced bone density is recognized as a predictor for potential complications in reverse shoulder arthroplasty (RSA). While humeral and glenoid planning based on preoperative computed tomography (CT) scans assist in implant selection and ...
Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification.
Scientific reports
Aug 13, 2024
Machine learning (ML) models have been increasingly employed to predict osteoporosis. However, the incorporation of hair minerals into ML models remains unexplored. This study aimed to develop ML models for predicting low bone mass (LBM) using health...
Artificial intelligence-enhanced opportunistic screening of osteoporosis in CT scan: a scoping Review.
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Jul 10, 2024
PURPOSE: This scoping review aimed to assess the current research on artificial intelligence (AI)--enhanced opportunistic screening approaches for stratifying osteoporosis and osteopenia risk by evaluating vertebral trabecular bone structure in CT sc...
Evaluation of fragility fracture risk using deep learning based on ultrasound radio frequency signal.
Endocrine
Jul 9, 2024
BACKGROUND: It was essential to identify individuals at high risk of fragility fracture and prevented them due to the significant morbidity, mortality, and economic burden associated with fragility fracture. The quantitative ultrasound (QUS) showed p...
Expanding Approaches to Improve Orthopaedic Care Through the Application of Artificial Intelligence: Commentary on an article by Neil P. Sheth, MD, et al.: "Effects of Abaloparatide on Bone Mineral Density in Proximal Femoral Regions Corresponding to Arthroplasty Gruen Zones. A Study of Postmenopausal Women with Osteoporosis".
The Journal of bone and joint surgery. American volume
Jul 3, 2024
A Machine Learning Framework for Screening Plasma Cell-Associated Feature Genes to Estimate Osteoporosis Risk and Treatment Vulnerability.
Biochemical genetics
Jun 19, 2024
Osteoporosis, in which bones become fragile owing to low bone density and impaired bone mass, is a global public health concern. Bone mineral density (BMD) has been extensively evaluated for the diagnosis of low bone mass and osteoporosis. Circulatin...
Deep learning for osteoporosis screening using an anteroposterior hip radiograph image.
European journal of orthopaedic surgery & traumatology : orthopedie traumatologie
Jun 19, 2024
PURPOSE: Osteoporosis is a common bone disorder characterized by decreased bone mineral density (BMD) and increased bone fragility, which can lead to fractures and eventually cause morbidity and mortality. It is of great concern that the one-year mor...
A comprehensive approach for osteoporosis detection through chest CT analysis and bone turnover markers: harnessing radiomics and deep learning techniques.
Frontiers in endocrinology
Jun 4, 2024
PURPOSE: The main objective of this study is to assess the possibility of using radiomics, deep learning, and transfer learning methods for the analysis of chest CT scans. An additional aim is to combine these techniques with bone turnover markers to...
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