Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Abstract: Objective: To explore the optimization of XGBoost algorithm parameters based on heuristic algorithms, thereby enhancing the classification accuracy of the algorithm. Methods: For the binary ...

To overcome the limitations of traditional roller-compacted concrete (RCC) compaction monitoring—which relies on macroscopic experiments, overlooks microscopic mechanisms, and lacks model ...

Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity and ...

这是你suan的第一个项目，每日电力负荷的时间序列预测模型,数据集格式模板为：'年/月/日 时:分'(year/month/day hour:minute ...

Researchers have developed a novel AI-driven framework using the XGBoost algorithm to accurately evaluate the skid resistance of asphalt pavements under various conditions. Published in Smart ...

The XGBoost-based approach demonstrated robust external validation across multiple centers, supporting clinical adoption to guide personalized treatment decisions. A machine learning (ML) model using ...

Background: Machine learning (ML) algorithms offer some advantages over traditional scoring systems to assess the influence of cardiovascular risk factors (CVRFs) on the risk of major cardiovascular ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...