By modeling the single-trial electroencephalogram of participants performing perceptual decisions, and building on predictions from two century-old psychological laws, we estimate the times of ...

Professor Klaus Nordhausen develops modern multivariate statistical methods to analyze high-dimensional and large datasets in different fields.

Objective Patients with atrial fibrillation (AF) frequently have multiple comorbidities that increase the risk of hospitalisation and contribute to higher mortality. However, studies examining the ...

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

Researchers have identified specific coupled patterns of brain activity and gene expression that help explain impulsive behavior in children with attention deficit hyperactivity disorder. By analyzing ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

ABSTRACT: This research examines the interrelationships among uncertainty avoidance (UA), entrepreneurial motivations, and entrepreneurial intention (EI) within the context of Vietnamese higher ...

Recent advances in green chemistry have made multivariate experimental design popular in sample preparation development. This approach helps reduce the number of measurements and data for evaluation ...

Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...

Scientists harnessed a new method to precisely measure the amount of information the brain can store, and it could help advance our understanding of learning. When you purchase through links on our ...