AI is rapidly transforming fertility care, from cycle tracking to embryo selection. The troubles arise when it is used to try ...

Unruly, undigital, and fiercely communal — the Gallagher Bros.' U.S. swing is everything our techno-entertainment world isn't ...

K-means remains a widely used algorithm due to its efficiency, although its performance can suffer in high ... 19 These themes are prevalent in clinical and population studies.20 For example, risk ...

Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...

ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...

The year 2024 is the time when most manual things are being automated with the assistance of Machine Learning algorithms. You’d be surprised at the growing number of ML algorithms that help play chess ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...

Abstract: The K-means algorithm is a partition-based clustering approach with two notable drawbacks, sensitivity to the initial center and a tendency to converge to suboptimal solutions. To address ...

This study aims to characterize the high frequency radar and numerically simulated low-frequency filtered currents in the south-eastern Bay of Biscay (study area) using a K-means classification ...