Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Meta on Wednesday debuted an AI feature called "Dear Algo" that lets Threads users personalize their content-recommendation algorithms. Threads users will be able to tell the Dear Algo tool what kinds ...

In April of 2023, when I was fresh out of a Ph.D. program in philosophy, I was hired as the nonfiction critic at the newly revived books section of the Washington Post. The shock to my system was ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Abstract: Currently, a wide array of clustering algorithms have emerged, yet many approaches rely on K-means to detect clusters. However, K-means is highly sensitive to the selection of the initial ...

Ballot (Balanced Lloyd with Optimal Transport) is a high-performance Python package for balanced clustering. It solves the problem of creating equal-sized clusters (or clusters with specific capacity ...

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...

Frigid temperatures are set to continue over the next several days before another blast of arctic air spreads from the Plains to the Southeast Friday, Jan. 30, into Saturday, Jan. 31, with record low ...