By using AI and IoT, manufacturers can now spot issues early, which stops downtime and keeps machines running longer.

Artificial Intelligence (AI) has evolved far beyond the initial waves of hype and the equally misplaced fears of machines ...

The increasing availability of educational data has paved the way for advanced data-driven approaches to enhance learning outcomes and decision-making. This paper explores the role of Predictive and ...

The decision in Recentive Analytics v. Fox Corp. is significant for patent attorneys and applicants in the AI space, particularly those seeking protection for inventions that incorporate machine ...

As data volumes surge across every industry and machine learning tools become more accessible, predictive analytics is evolving from a niche discipline into a cornerstone of application innovation.

Predictive modelling employing machine learning, convolutional neural networks (CNNs), and smartphone RGB images for non-destructive biomass estimation of pearl millet (Pennisetum glaucum) ...

Objective To determine how machine learning has been applied to prediction applications in population health contexts. Specifically, to describe which outcomes have been studied, the data sources most ...

Risk management is relevant for every project that which seeks to avoid and suppress unanticipated costs, basically calling for pre-emptive action. The current work proposes a new approach for ...

In DBTA's latest webinar, Stop Fixing, Start Predicting: Mastering Predictive Maintenance with IoT Data Analytics and AI, experts from OpenText explained how to implement a predictive maintenance ...

This article introduces a special issue on the interaction between the rapidly expanding field of machine learning and ongoing research in physics. The first half of the papers in this issue deals ...