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

Simulating how atoms and molecules move over time is a central challenge in computational chemistry and materials science.

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, ...

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

The integration of artificial intelligence (AI) and computational intelligence techniques has revolutionized biomedical signal processing by enabling more precise disease diagnostics and patient ...

Zoonova AI today announced the launch of Alpha AI, a new investing platform designed to make advanced market intelligence more accessible through a natural-language AI Command Center. Alpha AI ...

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, ...

With the rapid development of single-cell RNA sequencing (scRNA-seq), researchers can now examine gene activity in individual ...

Researchers at Institute of Industrial Science, The University of Tokyo  and George Mason University‘s College of Science have developed a new method that improves air temperature forecasts one to ...

Abstract: In this letter, a machine-learning-assisted graphic antenna design method using dynamic acquisition ensemble (ML-GDAE) is proposed. First, a dynamic normalized Gaussian network-based antenna ...

Thyroid cancer presents a significant clinical challenge due to asymptomatic onset and poor post-metastasis prognosis. Current imaging methods lack specificity, and single biomarkers show limited ...