Steroids

Multi-Omics Analysis by Machine Learning Identified Lysophosphatidic Acid as a Biomarker and Therapeutic Target for Porcine Reproductive and Respiratory Syndrome.

As a significant infectious disease in livestock, porcine reproductive and respiratory syndrome (PRR...

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...

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...

Machine Learning in Electroconvulsive Therapy: A Systematic Review.

Despite years of research, we are still not able to reliably predict who might benefit from electroc...

Machine learning survival prediction using tumor lipid metabolism genes for osteosarcoma.

Osteosarcoma is a primary malignant tumor that commonly affects children and adolescents, with a poo...

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...

A novel case-finding strategy based on artificial intelligence for the systematic identification and management of individuals with osteoporosis or at varying risk of fragility fracture.

UNLABELLED: An artificial intelligence-based case-finding strategy has been developed to systematica...

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 assessment of organ transplant operation: A fuzzy hybrid MCDM approach based on fuzzy FMEA.

Nowadays, most fatal diseases are attributed to the malfunction of bodily. Sometimes organ transplan...

Integration of bioinformatics and machine learning approaches for the validation of pyrimidine metabolism-related genes and their implications in immunotherapy for osteoporosis.

BACKGROUND: Osteoporosis (OP), the "silent epidemic" of our century, poses a significant challenge t...

Biomimetic piezoelectric nanomaterial-modified oral microrobots for targeted catalytic and immunotherapy of colorectal cancer.

Lactic acid (LA) accumulation in the tumor microenvironment poses notable challenges to effective tu...

Predicting Osteoporosis and Osteopenia by Fusing Deep Transfer Learning Features and Classical Radiomics Features Based on Single-Source Dual-energy CT Imaging.

RATIONALE AND OBJECTIVES: To develop and validate a predictive model for osteoporosis and osteopenia...

Creating machine learning models that interpretably link systemic inflammatory index, sex steroid hormones, and dietary antioxidants to identify gout using the SHAP (SHapley Additive exPlanations) method.

BACKGROUND: The relationship between systemic inflammatory index (SII), sex steroid hormones, dietar...

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

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

Comprehensive Review on the Virulence Factors and Therapeutic Strategies with the Aid of Artificial Intelligence against Mucormycosis.

Mucormycosis, a rare but deadly fungal infection, was an epidemic during the COVID-19 pandemic. The ...