Endocrinology

Osteoporosis

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

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Machine-learning models for diagnosis of rotator cuff tears in osteoporosis patients based on anteroposterior X-rays of the shoulder joint.

OBJECTIVE: This study aims to diagnose Rotator Cuff Tears (RCT) and classify the severity of RCT in ...

Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning.

INTRODUCTION: Metabolic syndrome (MetS) is considered to be an important parameter of cardio-metabol...

A Siamese Convolutional Neural Network for Identifying Mild Traumatic Brain Injury and Predicting Recovery.

Timely diagnosis of mild traumatic brain injury (mTBI) remains challenging due to the rapid recovery...

Artificial intelligence in coronary artery calcium score: rationale, different approaches, and outcomes.

Almost 35 years after its introduction, coronary artery calcium score (CACS) not only survived techn...

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide,...

Automatic Skeleton Segmentation in CT Images Based on U-Net.

Bone metastasis, emerging oncological therapies, and osteoporosis represent some of the distinct cli...

Integrated machine learning-based virtual screening and biological evaluation for identification of potential inhibitors against cathepsin K.

Cathepsin K is a type of cysteine proteinase that is primarily expressed in osteoclasts and has a ke...

Predicting osteoporosis from kidney-ureter-bladder radiographs utilizing deep convolutional neural networks.

Osteoporosis is a common condition that can lead to fractures, mobility issues, and death. Although ...

Application of machine learning algorithms to identify people with low bone density.

BACKGROUND: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individ...

Metabolic phenotyping with computed tomography deep learning for metabolic syndrome, osteoporosis and sarcopenia predicts mortality in adults.

BACKGROUND: Computed tomography (CT) body compositions reflect age-related metabolic derangements. W...

Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QC...

Machine learning reveals the control mechanics of an insect wing hinge.

Insects constitute the most species-rich radiation of metazoa, a success that is due to the evolutio...

Integrating machine learning models with cross-validation and bootstrapping for evaluating groundwater quality in Kanchanaburi province, Thailand.

Exploring the potential of new models for mapping groundwater quality presents a major challenge in ...

System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning.

The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous ne...

Influence of Deep Learning Based Image Reconstruction on Quantitative Results of Coronary Artery Calcium Scoring.

RATIONALE AND OBJECTIVES: To assess the impact of deep learning-based imaging reconstruction (DLIR) ...

Exploring the impact of pathogenic microbiome in orthopedic diseases: machine learning and deep learning approaches.

Osteoporosis, arthritis, and fractures are examples of orthopedic illnesses that not only significan...

Machine learning-aided search for ligands of P2Y and other P2Y receptors.

The P2Y receptor, activated by uridine diphosphate (UDP), is a target for antagonists in inflammator...

Identification of potential cell death-related biomarkers for diagnosis and treatment of osteoporosis.

BACKGROUND: This study aimed to identify potential biomarkers for the diagnosis and treatment of ost...

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