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Bone Density

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Valid inference for machine learning-assisted genome-wide association studies.

Nature genetics
Machine learning (ML) has become increasingly popular in almost all scientific disciplines, including human genetics. Owing to challenges related to sample collection and precise phenotyping, ML-assisted genome-wide association study (GWAS), which us...

Artificial intelligence assisted automatic screening of opportunistic osteoporosis in computed tomography images from different scanners.

European radiology
OBJECTIVES: It is feasible to evaluate bone mineral density (BMD) and detect osteoporosis through an artificial intelligence (AI)-assisted system by using quantitative computed tomography (QCT) as a reference without additional radiation exposure or ...

BoneScore: A natural language processing algorithm to extract bone mineral density data from DXA scans.

Health informatics journal
To develop and test an NLP algorithm that accurately detects the presence of information reported from DXA scans containing femoral neck T-scores of the patients scanned. A rule-based NLP algorithm that iteratively built a collection of regular exp...

Application of Machine Learning to Osteoporosis and Osteopenia Screening Using Hand Radiographs.

The Journal of hand surgery
PURPOSE: Fragility fractures associated with osteoporosis and osteopenia are a common cause of morbidity and mortality. Current methods of diagnosing low bone mineral density require specialized dual x-ray absorptiometry (DXA) scans. Plain hand radio...

Prediction of Bone Mineral Density based on Computer Tomography Images Using Deep Learning Model.

Gerontology
INTRODUCTION: The problem of population aging is intensifying worldwide. Osteoporosis has become an important cause affecting the health status of older populations. However, the diagnosis of osteoporosis and people's understanding of it are seriousl...

Utilizing artificial intelligence to determine bone mineral density using spectral CT.

Bone
BACKGROUND: Dual-energy computed tomography (DECT) has demonstrated the feasibility of using HAP-water to respond to BMD changes without requiring dedicated software or calibration. Artificial intelligence (AI) has been utilized for diagnosising oste...

HarDNet-based deep learning model for osteoporosis screening and bone mineral density inference from hand radiographs.

Bone
PURPOSE: Osteoporosis, affecting over 200 million individuals, often remains unrecognized and untreated, increasing the risk of fractures in older adults. Osteoporosis is typically diagnosed with bone mineral density (BMD) measured by dual-energy X-r...

Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis.

BMC musculoskeletal disorders
BACKGROUND: Osteoporosis is one of the most common metabolic diseases that is characterized by a decrease in bone density and a loss of the quality of the bone structure. The use of deep learning in the prediction of osteoporosis can provide a non-in...

Current status and dilemmas of osteoporosis screening tools: A narrative review.

Clinical nutrition ESPEN
OBJECTIVE: This review aims to explore the strengths and dilemmas of existing osteoporosis screening tools and suggest possible ways of optimization, in addition to exploring the potential of AI-integrated X-ray imaging in osteoporosis screening, esp...