AIMC Topic: Osteoporosis

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The Diagnostic Value of Image-Based Machine Learning for Osteoporosis: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Osteoporosis (OP) is projected to be a major issue significantly impacting the well-being of middle-aged and old populations. Machine learning (ML) and deep learning (DL) models developed based on medical imaging have enhanced clinicians'...

Cross-talk between diabetic nephropathy and bone loss: PBMCs-guided discovery of NLRP3-inflammatory signalling.

Artificial cells, nanomedicine, and biotechnology
Diabetic nephropathy (DN), a major driver of end-stage kidney disease, elevates the risk for osteoporosis (OP) and its clinical precursor, low bone mineral density (low BMD), indicating broader systemic effects. While peripheral blood mononuclear cel...

Effects of bisphosphonates after denosumab discontinuation and treatment effect heterogeneity using causal machine learning.

Scientific reports
Discontinuation of denosumab is associated with a rebound increase in osteoporotic fracture (OF) risk, and bisphosphonates (BPs) are commonly recommended as sequential therapy to mitigate this risk. However, their real-world effectiveness-and whether...

Unraveling the Mechanisms of Osteoporosis Triggered by Methylparaben and Monomethyl Phthalate through Integrated Mendelian Randomization, In Silico Simulations, and Experimental Validation.

Environmental science & technology
Endocrine-disrupting chemicals (EDCs) are pervasive environmental hazards that have been linked to osteoporosis (OP), though causal mechanisms remain elusive. Employing an integrated multiomics framework, this study combined bidirectional Mendelian r...

Machine Learning Models To Characterize the Association of the Gut Microbiota with Osteopenia and Osteoporosis: A Multi-Cohort Study.

Current microbiology
Emerging evidence suggests that gut microbiota dysbiosis is associated with bone metabolism disorders, including osteopenia (ON) and osteoporosis (OP). However, multi-cohort integrated and association analyses remain underexplored. We conducted a com...

Face2Bone explainable AI model predicts osteoporosis risk from facial images in proof of concept study.

Scientific reports
OBJECTIVES: BMI and age are associated with the risk of osteoporosis (OP). The dynamic facial aging process involves changes in skin, muscle, fat, and facial bone structures, with facial skeletal aging affecting facial contours through volumetric red...

Introducing FREM: a decision-support approach for automated identification of individuals at high imminent fracture risk.

Archives of osteoporosis
UNLABELLED: This study used explainable AI to improve the Danish FREM model for predicting one-year risk of major osteoporotic fractures in over 2.4 million individuals aged ≥ 45. A DART boosting algorithm improved performance (AUC 0.77), with explai...

Deep‑learning based osteoporosis classification in knee X‑rays using transfer‑learning approach.

Scientific reports
Bone deterioration from osteoporosis creates fractures that primarily affect females who have reached menopause and older adults. Early detection of osteoporosis requires affordable methods because current diagnostic systems are both expensive and ch...

A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region.

Scientific reports
Improving accuracy and timeliness for osteoporosis diagnosis could help prevent fragility fractures, morbidity, and mortality for older individuals. Osteoporosis is an often silent health condition, especially as regards vertebral fractures, and WHO ...