Abstract: This paper aims to investigate the efficacy of EEG-based stress detection using a Random Forest classifier during the Stroop Test, a key psychological assessment probing cognitive functions ...

With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

CERES program updates include operational satellite instruments, algorithm advancements, machine learning applications, and ongoing missions measuring Earth’s energy budget and climate system changes.

Researchers have uncovered nearly 150 hidden DNA “switches” inside brain support cells that control the activity of genes ...

A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...

A new study published in the International Journal of General Medicine showed that physicians may reliably estimate the ...

Abstract: Reliable estimation of rainfall is vital for framing, hydrological management, and risk mitigation, particularly in areas where local climate conditions significantly influence the weather.

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

ABSTRACT: Meditation offers a controlled behavioral context for probing attention, arousal, and self-regulation. Rather than positioning the present work as a discovery of novel neural signatures, we ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.