Osteoporosis

AI Screening Tool Based on X-Rays Improves Early Detection of Decreased Bone Density in a Clinical Setting.

PURPOSE: Osteoporosis is an under-screened musculoskeletal disorder that results in diminished quality of life and significant burden to the healthcare system. We aimed to evaluate the ability of Rho, an artificial intelligence (AI) tool, to prospectively identify patients at-risk for low bone mineral density (BMD) from standard x-rays, its adoption rate by radiologists, and acceptance by primary ...

Development of a High-Performance Ultrasound Prediction Model for the Diagnosis of Endometrial Cancer: An Interpretable XGBoost Algorithm Utilizing SHAP Analysis.

OBJECTIVES: To develop and validate an ultrasonography-based machine learning (ML) model for predicting malignant endometrial and cavitary lesions. METHODS: This retrospective study was conducted on patients with pathologically confirmed results following transvaginal or transrectal ultrasound from 2021 to 2023. Endometrial ultrasound features were characterized using the International Endometrial...

Artificial Intelligence Deep Learning Ultrasound Discrimination of Cosmetic Fillers: A Multicenter Study.

OBJECTIVES: Despite the growing use of artificial intelligence (AI) in medicine, imaging, and dermatology, to date, there is no information on the use...

An AI-based pipeline for osteoporosis/osteopenia prediction using hip radiographs.

OBJECTIVE: To develop and validate an artificial intelligence-based tool for the diagnosis of osteoporosis/osteopenia using hip radiographs. The tool ...

A biologically plausible model of astrocyte-neuron networks in random and hub-driven connectivity.

Recent research studies in brain neural networks are highlighting the involvement of glial cells, in particular astrocytes, in synaptic modulation, me...

Interrogating functional connectivity of in vitro neural glia tissue model modulated through integrative control of matrix stiffness and a neurotrophic factor.

Brain function emerges from intricate cellular communication within neural networks. Both In silico neuronal models and primary neuron cells have reve...

Digital versus analogue PET in parathyroid imaging: comparison of PET metrics and machine learning-based characterisation of hyperfunctioning lesions (the DIGI-PET study).

PURPOSE: To compare PET-derived metrics between digital and analogue PET/CT in hyperparathyroidism, and to assess whether machine learning (ML) applie...

Multicenter Machine Learning-Based Prediction of Mortality in ICU Patients With Hypocalcemia.

BACKGROUND: Hypocalcemia occurs frequently in intensive care units (ICUs) and is independently associated with excess mortality. Conventional severity...

A machine learning platform for genotype-specific cardiotoxicity risk prediction using patient-derived iPSC-CMs.

INTRODUCTION: Drug-induced Torsades de Pointes (TdP) has led to withdrawal of several drugs from the market. Individuals with inherited cardiac channe...

Incidental Finding of Coronary and Non-Coronary Artery Calcium: What Do Clinicians Need To Know?

PURPOSE OF REVIEW: This review summarizes the role of incidentally and non-incidentally discovered coronary artery calcification (CAC) and the evolvin...

Deep learning algorithm for identifying osteopenia/osteoporosis using cervical radiography.

Due to symptomatic gait imbalance and a high incidence of falls, patients with cervical disease-including degenerative cervical myelopathy-have a sign...

A novel dual embedding few-shot learning approach for classifying bone loss using orthopantomogram radiographic notes.

BACKGROUND: Orthopantomograms (OPGs) are essential diagnostic tools in dental and maxillofacial care, providing a panoramic view of the jaws, teeth, a...

Analysis of Protein-Protein Interactions in CC125 by Co-Fractionation Mass Spectrometry.

, a unicellular eukaryotic green alga, is an important biological model. Previous studies on protein complexes in have primarily focused on photosynt...

Bridging molecular and cellular neuroscience with proximity labeling technologies.

Proximity labeling (PL) techniques have advanced neuroscience by revealing the molecular interactions that govern neural circuits. From foundational t...

Machine Learning-Assisted Development of Injectable, Mechanically Robust, and Energy Metabolism-Modulating Brushite Cements.

In orthopedic minimally invasive surgeries (MIS) such as percutaneous vertebroplasty (PVP) and percutaneous kyphoplasty (PKP), calcium phosphate cemen...

Development of Artificial Intelligence-Assisted Lumbar and Femoral BMD Estimation System Using Anteroposterior Lumbar X-Ray Images.

The early detection and treatment of osteoporosis and prevention of fragility fractures are urgent societal issues. We developed an artificial intelli...

Machine learning identifies KRT8 dysregulation and endothelial remodeling in Moyamoya disease.

Moyamoya disease (MMD) is a rare occlusive cerebrovascular disease, and its pathological mechanism remains unclear at present. The abnormal vascular r...

Improving prediction of fragility fractures in postmenopausal women using random forest.

Osteoporosis is a chronic disease characterized by a progressive decline in bone density and quality, leading to increased bone fragility and a higher...

Early transcriptional responses reveal cell type-specific vulnerability and neuroprotective mechanisms in the neonatal ischemic hippocampus.

Neonatal hypoxic-ischemic (H-I) brain injury, a leading cause of neurodevelopmental disabilities, severely affects the metabolically active and neurog...

Quantitative CT Imaging in Chronic Obstructive Pulmonary Disease.

Chronic obstructive pulmonary disease (COPD) is a highly heterogeneous condition characterized by diverse pulmonary and extrapulmonary manifestations....