AIMC Topic: Osteoporosis

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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 ...

Exploration of autophagy-associated genes and potential molecular mechanisms in type 1 diabetes and osteoporosis.

Scientific reports
The co-occurrence of osteoporosis (OP) and type 1 diabetes mellitus (T1DM) represents a clinically significant comorbidity pattern, characterized by skeletal fragility and insulin deficiency. While epidemiological links exist, their shared molecular ...

Advancements in deep learning-based image screening for orthopedic conditions: Emphasis on osteoporosis, osteoarthritis, and bone tumors.

Ageing research reviews
Artificial intelligence (AI) has garnered increasing attention in the medical field. As the core technology of AI, deep learning (DL) has been extensively applied to the imaging-based screening of orthopedic diseases, primarily including image classi...

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...