Data mining is a process that turns large volumes of raw data into actionable intelligence, and it's used by a wide variety ...

The editorial board members (AHA) journals are committed to transparency, open-science principles, and quality assurance in the publication of AI-based research articles, with the goal of achieving ...

Abstract: Clustering analysis has been widely applied in various fields, and boundary detection based clustering algorithms have shown effective performance. In this work, we propose a clustering ...

Tim Berners-Lee may have the smallest fame-to-impact ratio of anyone living. Strangers hardly ever recognize his face; on “Jeopardy!,” his name usually goes for at least sixteen hundred dollars.

Objectives: This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold ...

PRINCETON, N.J.--(BUSINESS WIRE)--$BMY #BMS--Bristol Myers Squibb (NYSE: BMY) today announced that the Phase 3 EXCALIBER-RRMM study evaluating iberdomide, an ...

The Trump administration is re-evaluating a $2.3 billion loan approved by President Joe Biden for the development of a Nevada lithium deposit, according to people familiar with the matter who asked ...

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DJ Moore finally found the end zone in Chicago’s Week 3 victory over the Dallas Cowboys. However, the veteran wideout has failed to live up to his preseason lofty expectations. Heading into the final ...

Abstract: Data stream clustering reveals patterns within continuously arriving, potentially unbounded data sequences. Numerous data stream algorithms have been proposed to cluster data streams. The ...