Integrating radiomics with clinical data for enhanced prediction of vertebral fracture risk.

Introduction: Osteoporotic vertebral fractures are a major cause of morbidity, disability, and mortality among the elderly. Traditional methods for fracture risk assessment, such as dual-energy X-ray absorptiometry (DXA), may not fully capture the complex factors contributing to fracture risk. This study aims to enhance vertebral fracture risk prediction by integrating radiomics features extracted from computed tomography (CT) scans with clinical data, utilizing advanced machine learning techniques.

Clinical and Radiological Outcome of Disc Arthroplasty for the Treatment of Cervical Spondylotic Myelopathy.

Introduction: The aim of this study is to evaluate the clinical and radiological results of cervical disc arthroplasty (CDA) in patients with cervical spondylotic myelopathy (CSM) using the CP ESP disc prosthesis.

Materials And Methods: Prospectively collected data of 56 patients with CSM have been analyzed. The mean age at surgery was 35.

Artificial Intelligence-Based Prediction of Oroantral Communication after Tooth Extraction Utilizing Preoperative Panoramic Radiography.

Oroantral communication (OAC) is a common complication after tooth extraction of upper molars. Profound preoperative panoramic radiography analysis might potentially help predict OAC following tooth extraction. In this exploratory study, we evaluated n = 300 consecutive cases (100 OAC and 200 controls) and trained five machine learning algorithms (VGG16, InceptionV3, MobileNetV2, EfficientNet, and ResNet50) to predict OAC versus non-OAC (binary classification task) from the input images.

Artificial Intelligence-Driven Prediction Modeling and Decision Making in Spine Surgery Using Hybrid Machine Learning Models.

Healthcare systems worldwide generate vast amounts of data from many different sources. Although of high complexity for a human being, it is essential to determine the patterns and minor variations in the genomic, radiological, laboratory, or clinical data that reliably differentiate phenotypes or allow high predictive accuracy in health-related tasks. Convolutional neural networks (CNN) are increasingly applied to image data for various tasks.