Consequently, speech can be a crucial modality in the initial phase of Parkinson’s disease prediction. In literature, diverse Machine Learning models are employed for Parkinson’s disease diagnosis ...

Abstract. Integrating Machine Learning into Statistical Methods in Disease Risk Prediction Modeling: A Systematic Review. Background: Disease prediction models often use statistical methods or machine ...

MILTON's disease prediction models are defined based on the time lag between biomarker sample collection and diagnosis. In the UKB, samples may have been collected up to 16.5 years before or 50 ...

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In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and ...

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the ...

Integrating machine learning (ML) models with selected features improved the prediction accuracy of diabetic kidney disease compared to traditional logistic regression models using established ...