The search for next-generation electronic materials often starts with studying the Fermi surface, which serves as a map of a ...

Depression, one of the most widespread mental health disorders, is characterized by a persistent low mood and a loss of ...

Python remains the go-to language for mastering machine learning, offering a rich ecosystem of libraries, frameworks, and real-world projects to build practical skills. From predictive maintenance to ...

Combining machine learning and feature selection, this research accurately predicts aluminum levels in marine environments, ...

A new review in Science China Life Sciences examines how machine learning and host-microbiome multi-omics can be combined to better understand health and disease. The article outlines the road from ...

Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...

Researchers have developed a feature selection-based solar irradiance forecasting method to improve the operation of ...

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 ...

A total of 8,598 children were enrolled and classified into three groups: ADHD (n=3,678), subthreshold ADHD (s-ADHD) (n=1,495), and healthy controls (HC) (n=3,425). Data collection covered 40 ...

Abstract: Accurate battery lifetime estimation is crucial for health management and system safety. Data-driven research yields extensive feature sets, yet optimal feature selection is often impeded by ...