Craniofacial morphometrics in sharks provide crucial insights into evolutionary history, geographical variation, sexual dimorphism, and developmental patterns. However, the fragile cartilaginous nature of shark craniofacial skeleton poses significant...
By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley (Hordeum Vulgare L). A 130-line F8-F9 barley population caused Badia and Kavir to grow at the Gonbad K...
Real-time synchronization for the servo system becomes one of the most popular themes in the Industry 4.0 era. Each connected agent publishes its data and mutual information in the shared protocol while host station plays a role as coordinator among ...
Precise demand forecasting has become crucial for merchants due to the growing complexity of client behavior and market dynamics. This allows them to enhance inventory management, minimize instances of stock outs, and enhance overall operational effi...
Mulberry leaf disease detection is vital for maintaining the health and productivity of mulberry crops. In this paper, a novel approach was proposed by integrating explainable artificial intelligence (XAI) techniques with a convolutional neural netwo...
Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly population. The early detection of mild cognitive impairment (MCI) holds significant clinical importance for prompt intervention and treatment of AD....
In order to further improve the injection precision of the PH300 insulin pump, this paper optimizes and improves the mechanical structure and control algorithm of the PH300. The improved PH300 uses a proportional-integral-derivative controller based ...
The inferential results regarding estimates of Support Vector Regression (SVR) are highly influenced by anomalies and ill-conditioned predictors. Excessive dimensions of data also make the model complex. To improve estimation accuracy, this paper int...
The accurate modeling of dynamic systems, particularly robotic ones, is crucial in the industry. It enables simulation-based approaches that facilitate various tasks without requiring the physical system, thereby reducing risks and costs. These appro...
International journal of medical informatics
Jun 3, 2025
BACKGROUND AND OBJECTIVE: To develop and validate a machine learning model based on stacking ensemble learning and feature selection strategies to predict vertebral refracture risk after percutaneous vertebroplasty.
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