Abstract: Sparse and unevenly distributed soil samples across the northern high-latitude region greatly limit the accuracy of soil organic carbon (SOC) mapping. Substantial discrepancies, therefore, ...

ABSTRACT: This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates ...

This study evaluates the effect of common resampling strategies on imbalanced binary classification by benchmarking multiple classifiers—including linear models, distance-based methods, tree learners, ...

A U.S. Postal Service employee died after he became stuck inside a mail handling machine at a distribution center in Allen Park, Michigan, according to officials. Nicholas John Acker, 36, was stuck in ...

ABSTRACT: This study presents a comprehensive clinical decision support system aimed at personalizing antidepressant treatment selection using synthetic patient data, predictive modelling, and ...

LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing method robustness in 2D LC, practical approaches for tracking peaks across ...

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. Inverse protein folding is a critical ...

Abstract: Machine learning algorithms face important implementation difficulties due to imbalanced learning since the Synthetic Minority Oversampling Technique (SMOTE) helps improve performance ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...