A recent analysis of a major developmental dataset reveals that children who play musical instruments over several years ...

A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture has surged. Ionic liquids (ILs) ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

While machine learning can sharpen coronary artery disease (CAD) prediction using standard clinical data, it falls short in detecting plaques most likely to cause future cardiac events in patients ...

Abstract: The rapid increase in cyber threats has heightened the demand for Intrusion Detection Systems (IDS) that are both accurate and efficient. While deep learning models outperform traditional ...

The ML model stratifies HCC patients by mortality risk, guiding treatment decisions between liver transplantation and surgical resection. The model demonstrated improved survival outcomes, with a 54% ...

Differential privacy (DP) stands as the gold standard for protecting user information in large-scale machine learning and data analytics. A critical task within DP is partition selection—the process ...

Abstract: Cloud detection is a crucial preliminary step for assimilating meteorological satellite observation and retrieving other atmospheric parameters. This article presents an explainable machine ...