Frontiers

Explainable machine learning for early detection of Parkinson’s disease in aging populations using vocal biomarkers

1 Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan 2 School of Information Technology and Systems, University of ...
IEEE

Fault Diagnosis for Transformer Winding using Morpho-offset Feature of Oscillating Wave and CPO-XGBoost Algorithm

Abstract: Accurate and effective diagnosis of transformer winding conditions is crucial for ensuring their safe and reliable operation. This paper proposes a transformer winding fault detection method ...
Frontiers

Enhancing sleep stage classification with ballistocardiogram signals: feature selection using attention mechanism and XGBoost

1 School of Information Engineering, Huzhou University, Huzhou, China 2 Key Laboratory of Artificial Organs, Computational Medicine in Zhejiang Province, College of Information Science and Technology, ...
ascopubs.org

Prediction of Patients With High-Risk Osteosarcoma on the Basis of XGBoost Algorithm Using Transcriptome and Methylation Data From SGH-OS Cohort

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 ...
Scientific Research Publishing

Kibria, H.B., Nahiduzzaman, M., Goni, M.O.F., Ahsan, M. and Haider, J. (2022) An Ensemble Approach for the Prediction of Diabetes Mellitus Using a Soft Voting Classifier with ...

ABSTRACT: The early detection of type 2 diabetes is a major challenge for healthcare professionals, as a late diagnosis can lead to severe and difficult-to-manage complications. In this context, this ...
Scientific Research Publishing

Kumari, S., Kumar, D. and Mittal, M. (2021) An Ensemble Approach for Classification and Prediction of Diabetes Mellitus Using Soft Voting Classifier. International Journal of ...

ABSTRACT: The early detection of type 2 diabetes is a major challenge for healthcare professionals, as a late diagnosis can lead to severe and difficult-to-manage complications. In this context, this ...
IEEE

Performance Analysis of Support Vector Machine and Xgboost Classifier Algorithms in Predicting Data Heart Disease

Abstract: Heart disease is a common condition in humans and can have a negative impact on health. Various data such as age, gender, blood pressure, and other factors can be utilized to predict the ...