Osteoporosis

Predicting ultrasound wave stimulated bone growth in bioinspired scaffolds using machine learning.

For conditions like osteoporosis, changes in bone pore geometry even when porosity is constant have ...

Preventive machine learning models incorporating health checkup data and hair mineral analysis for low bone mass identification.

Machine learning (ML) models have been increasingly employed to predict osteoporosis. However, the i...

Accurate neuron segmentation method for one-photon calcium imaging videos combining convolutional neural networks and clustering.

One-photon fluorescent calcium imaging helps understand brain functions by recording large-scale neu...

Establishing a Classification System for Predicting Flow-Limiting Dissection After Balloon Angioplasty Using Explainable Machine-Learning Models: A Multicenter Retrospective Cohort Study.

OBJECTIVE: Percutaneous transluminal angioplasty (PTA) is the primary method for treatment in periph...

Comparative analysis of vision transformers and convolutional neural networks in osteoporosis detection from X-ray images.

Within the scope of this investigation, we carried out experiments to investigate the potential of t...

Deep learning application of vertebral compression fracture detection using mask R-CNN.

Vertebral compression fractures (VCFs) of the thoracolumbar spine are commonly caused by osteoporosi...

Artificial intelligence-enhanced opportunistic screening of osteoporosis in CT scan: a scoping Review.

PURPOSE: This scoping review aimed to assess the current research on artificial intelligence (AI)--e...

Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra.

Raman spectroscopy is a rapid method for analysing the molecular composition of biological material....

Prediction of arsenic concentration in groundwater of Chapainawabganj, Bangladesh: machine learning-based approach to spatial modeling.

Groundwater in northwestern parts of Bangladesh, mainly in the Chapainawabganj District, has been co...

Predictive modeling of lower extreme deep vein thrombosis following radical gastrectomy for gastric cancer: based on multiple machine learning methods.

Postoperative venous thromboembolic events (VTEs), such as lower extremity deep vein thrombosis (DVT...

Expanding Approaches to Improve Orthopaedic Care Through the Application of Artificial Intelligence: Commentary on an article by Neil P. Sheth, MD, et al.: "Effects of Abaloparatide on Bone Mineral Density in Proximal Femoral Regions Corresponding to Arthroplasty Gruen Zones. A Study of Postmenopausal Women with Osteoporosis".

Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study.

BACKGROUND: The reaserch of artificial intelligence (AI) model for predicting spinal refracture is l...

Rapid diagnosis of celiac disease based on plasma Raman spectroscopy combined with deep learning.

Celiac Disease (CD) is a primary malabsorption syndrome resulting from the interplay of genetic, imm...

Identifying factors associated with locomotive syndrome using machine learning methods: The third survey of the research on osteoarthritis/osteoporosis against disability study.

AIM: To identify factors associated with locomotive syndrome (LS) using medical questionnaire data a...

The potential role for artificial intelligence in fracture risk prediction.

Osteoporotic fractures are a major health challenge in older adults. Despite the availability of saf...

Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to .

(Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economica...

Deep learning for osteoporosis screening using an anteroposterior hip radiograph image.

PURPOSE: Osteoporosis is a common bone disorder characterized by decreased bone mineral density (BMD...

Enhancing trabecular CT scans based on deep learning with multi-strategy fusion.

Trabecular bone analysis plays a crucial role in understanding bone health and disease, with applica...

A comprehensive approach for osteoporosis detection through chest CT analysis and bone turnover markers: harnessing radiomics and deep learning techniques.

PURPOSE: The main objective of this study is to assess the possibility of using radiomics, deep lear...

Identification of shared gene signatures and pathways for diagnosing osteoporosis with sarcopenia through integrated bioinformatics analysis and machine learning.

BACKGROUND: Prior studies have suggested a potential relationship between osteoporosis and sarcopeni...

Development of UroSAM: A Machine Learning Model to Automatically Identify Kidney Stone Composition from Endoscopic Video.

Chemical composition analysis is important in prevention counseling for kidney stone disease. Advan...