This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...

Despite significant mathematical refinements, econometrics has shown the weaknesses of its logical underpinnings, primarily during economic turning points—financial crises, pandemics, and geopolitical ...

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

Read more about AI and machine learning drive digital transformation across global mining operations on Devdiscourse ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...

Google published a research paper on how to extract user intent from user interactions that can then be used for autonomous agents. The method they discovered uses on-device small models that do not ...

Biobased 2,3-butanediol (2,3-BDO) is a valuable biomass-derived chemical due to its versatility in being transformed into a wide variety of products. However, the separation and purification of ...

Abstract: The increasing penetration of inverter-based distributed generation (DG) into power grids improves access to electricity and provides a significant possibility for decarbonization. However, ...

Abstract: This research investigates the transformative role of machine learning (ML) in automating knowledge extraction (AKE) from unstructured text data, a critical challenge in the era of big data.

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...

The landscape of psychological and social science research is undergoing a profound transformation, and the catalyst is clear: the integration of data science and machine learning methodologies. As ...