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Abstract: Financial statement fraud (FSF) is a challenging issue in capital markets and severely affects their overall health and stability. The effective prediction of FSF has become an urgent need ...

Abstract: In this article, we propose using new machine learning (ML)-based optimization methods as an alternative to traditional optimization methods, for complex antenna designs. This is an ...

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

Objective: In this study, we applied machine learning techniques to construct a medical database system from electronic medical records (EMRs) of subjects who have undergone health examination. This ...

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...

Open-Source AI Tools while not widely publicized, are highly regarded within the developer community for their ability to simplify complex tasks ...

This review explains how soft materials, scalable manufacturing, energy-efficient hardware, and AI are converging to create ...

Conclusions: The prediction accuracy that we have achieved using this machine learning process suggests that we are able to predict, from free-text, a reasonably accurate assessment of patients’ ...

While recent national discussions, such as the NSF Artificial Intelligence Scholarship for Service (AI SFS), emphasize ...