Endocrinology

Osteoporosis

Latest AI and machine learning research in osteoporosis for healthcare professionals.

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DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health Records

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited therapeutic options. T...

Deep Learning-Based Opportunistic CT Osteoporosis Screening and Establishment of Normative Values

Osteoporosis is underdiagnosed and undertreated prompting the exploration of opportunistic screening...

Exploring Novel Biomarkers for Early Detection of Osteoporosis

Osteoporosis is characterized by diminished BMD and deteriorated bone microstructure, significantly ...

Incremental diagnostic value of AI-derived coronary artery calcium in 18F-flurpiridaz PET Myocardial Perfusion Imaging

Positron Emission Tomography (PET) myocardial perfusion imaging (MPI) is a powerful tool for predict...

The REgistry of Flow and Perfusion Imaging for Artificial INtelligEnce with PET (REFINE PET): Rationale and Design

The REgistry of Flow and Perfusion Imaging for Artificial INtelligEnce with PET (REFINE PET) was est...

Machine learning algorithm to predict fragility fractures and identification of important features – an explainable approach

In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence...

Using deep learning to improve genetic studies of osteoporosis

To evaluate how recent advances in deep learning can improve the construction of quantitative phenot...

Development of Self-Assessment Tools for Osteoporosis among Postmenopausal Vietnamese Women: A Machine Learning Approach

Osteoporosis is a major health concern in Vietnam due to a rise in aging rates. However, cost-effect...

Large language models in radiologic numerical tasks: A thorough evaluation and error analysis

To investigate the performance of LLMs in radiology numerical tasks and perform a comprehensive erro...

Development of a Multi-Model Ensemble Tool for Early Prediction of 48-Hour Respiratory Failure Risk in CAP Patients

To develop a predictive tool capable of early identification of the risk of acute respiratory failur...

Artificial intelligence for aortic valve calcium score quantification by echocardiography

Aortic valve calcification (AVC), as measured by gold-standard computed tomography (CT) Agatston sco...

A framework for identifying calcium accumulation problem in cropland: Integrating field surveys, legacy soil map, and machine learning models.

The calcium accumulation problem (CAP) in cinnamon soil regions of northern China significantly impa...

Jan 2025 40445970
Exploring the Mechanisms of Sanguinarine in the Treatment of Osteoporosis by Integrating Network Pharmacology Analysis and Deep Learning Technology.

BACKGROUND: Sanguinarine (SAN) has been reported to have antioxidant, antiinflammatory, and antimicr...

Jan 2025 38385487
DeepTransformer: Node Classification Research of a Deep Graph Network on an Osteoporosis Graph based on GraphTransformer.

BACKGROUND: Osteoporosis (OP) is one of the most common diseases in the elderly population. It is mo...

Jan 2025 39651564
Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS).

INTRODUCTION: In Iran, the assessment of osteoporosis through tools like dual-energy X-ray absorptio...

Jan 2025 39760233
An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling

Vertebral compression fractures (VCFs) are a common and potentially serious consequence of osteopo...

Computer-Aided Osteoporosis Diagnosis Using Transfer Learning with Enhanced Features from Stacked Deep Learning Modules

Knee osteoporosis weakens the bone tissue in the knee joint, increasing fracture risk. Early detec...

Osteoporosis Prediction from Hand X-ray Images Using Segmentation-for-Classification and Self-Supervised Learning

Osteoporosis is a widespread and chronic metabolic bone disease that often remains undiagnosed and...

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