A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Abstract: The deviation settlement mechanism (DSM) scheme enforces strict regulations on microgrid operators to comply with generation commitment norms set by grid operators. These norms are essential ...

This is the preface for the book by E. N. Dzhafarov, J. V. Kujala, and V. H. Cervantes, titled Contextuality in Random Variables: A Systematic Introduction. It is to be published by Cambridge ...

A courseware module that covers the fundamental concepts in probability theory and their implications in data science. Topics include probability, random variables, and Bayes' Theorem.

There are many methods available to fit random-effects meta-analysis. However, until 2024, the only option available in RevMan has been the DerSimonian and Laird random-effects method. This method is ...

Abstract: This work considers the notion of random tensors and reviews some fundamental concepts in statistics when applied to a tensor based data or signal. In several engineering fields such as ...

Amid efforts to address energy consumption in modern computing systems, one promising approach takes advantage of random networks of non-linear nanoscale junctions formed by nanoparticles as ...

Department of the Rehabilitation Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China Background: Inflammation and liver function are associated with ...

ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...