Combining machine learning and feature selection, this research accurately predicts aluminum levels in marine environments, ...
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 ...
Opinion
10dOpinion
How do different data preprocessing techniques affect performance of machine learning models on prediction tasks?
Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...
Background Hypertrophic cardiomyopathy (HCM) is associated with an increased risk of sudden cardiac death (SCD), and myocardial fibrosis plays a central role in the pathophysiology process.
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 ...
However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
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 ...
Abstract: When the heart is unable to pump blood as effectively as it ought to, heart failure occurs. Breathing difficulty is frequently brought on by this because blood frequently backs up and fluid ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results