AIMC Topic: Bone Density

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Assessment of the risk of osteoporotic bone fracture in postmenopausal women using machine learning methods.

Scientific reports
The main objective of osteoporosis management is to prevent osteoporotic fractures. Using machine learning methods, new risk variables can be identified to enhance the ability to identify women with osteoporosis who are at an increased risk of bone f...

Construction and validation of a multi-dimensional health indicator-driven osteoporosis risk prediction model: a large-sample cross-sectional study based on two centers.

BMC musculoskeletal disorders
BACKGROUND: Rising osteoporosis prevalence among elderly populations and limitations of current single-factor screening methods necessitate development of comprehensive multi-dimensional risk prediction models.

BONE-Net: A novel hybrid deep-learning model for effective osteoporosis detection.

PloS one
Osteoporosis is a prevalent bone disease characterized by reduced bone density and an elevated risk of fractures, especially in older adults and postmenopausal women. The clinical consequences of osteoporotic fractures extend beyond pain and disabili...

Opportunistic screening of low bone mass using knowledge distillation-based deep learning in chest X-rays with external validations.

Archives of osteoporosis
UNLABELLED: Low bone mass (LBM), which can lead to osteoporosis, is often undetected and increases the risk of bone fractures. This study presents OsPenScreen, a deep learning model that can identify low bone mass early using standard chest X-rays (C...

Osteoporosis prediction from hand X-ray images using segmentation-for-classification and self-supervised learning.

Scientific reports
Osteoporosis is a prevalent metabolic bone disease that frequently remains undiagnosed due to limited access to bone mineral density (BMD) tests, such as Dual-energy X-ray absorptiometry (DXA). To address this issue, recent research explores alternat...

Association between fat-to-muscle ratio and secondary osteoporosis in rheumatoid arthritis: a cross-sectional study at a tertiary hospital in China.

BMJ open
OBJECTIVES: To investigate the correlation between fat-to-muscle ratio (FMR) or other body composition and secondary osteoporosis (OP) in patients with rheumatoid arthritis (RA) and to develop a predictive model using FMR and related clinical factors...

Fusion of X-Ray Images and Clinical Data for a Multimodal Deep Learning Prediction Model of Osteoporosis: Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Osteoporosis is a bone disease characterized by reduced bone mineral density and mass, which increase the risk of fragility fractures in patients. Artificial intelligence can mine imaging features specific to different bone densities, sha...

AI-driven bone mineral density prediction from chest x-rays and its association with obstructive sleep apnea.

PloS one
With an increasing aging population, the prevalence of chronic comorbidities is on the rise. The potential relationship between obstructive sleep apnea (OSA) and osteoporosis has garnered significant attention. Most studies examining the association ...

Opportunistic computed tomography (CT) assessment of osteoporosis in patients undergoing transcatheter aortic valve replacement (TAVR).

Archives of osteoporosis
UNLABELLED: CT-based opportunistic screening using artificial intelligence finds a high prevalence (43%) of osteoporosis in CT scans obtained for planning of transcatheter aortic valve replacement. Thus, opportunistic screening may be a cost-effectiv...

Artificial intelligence-based diabetes risk prediction from longitudinal DXA bone measurements.

Scientific reports
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 disea...