Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...

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 ...

Municipal Solid Waste Generation (MSWG) presents a significant challenge for sustainable urban development, with waste production escalating at alarming rates worldwide. To address this issue, ...

Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...

Abstract: Objective: This study aims to explore the optimization of XGBoost algorithm parameters based on heuristic algorithms, with the goal of improving the classification accuracy of the ...

Abstract: This paper investigates the prediction of sailboat prices using the LS-SVM prediction algorithm and the XGBoost algorithm. The study involves training ...

This study introduces the XGBoost Multimodal Autism Predictor (XMAP), an interpretable machine learning framework designed to improve ASD classification by integrating publicly available behavioral ...

1 Department of Electrical Engineering, School of Mechatronics and Information Engineering, Putian University, Putian, China 2 State Grid Sanming Electric Power Supply Company, Sanming, China Power ...