Researchers at Trinity College Dublin have found that a machine learning model could help clinicians predict which people with depression are more likely to improve with digital cognitive behavioral ...

Ad fraud is no longer a fringe issue. It is a systemic threat to digital advertising, and its scale demands a technological ...

Abstract: This paper deals with an innovative solution for tackling the problem of automobile procurement decision-making in the two-wheeler industry in India by utilizing ML techniques with the help ...

Overview Data science is one of the fastest-growing career fields today. Many colleges in India now offer courses in data science, AI, and machine learning.&nbs ...

Rachael Hinkle’s work with machine learning intersects political science, legal training and computational methods.

Soft Computing (SC) is an Artificial Intelligence (AI) approach that is more effective at solving real-life problems than traditional computing models. Soft Computing models are tolerant of partial ...

Abstract: Image recognition, powered by machine learning (ML), has significantly advanced applications in both dance movement recognition and robotic vision. This review examines key ML techniques, ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

Artificial intelligence is becoming an increasingly visible part of modern healthcare technology. Hospitals, research institutions, and healthcare organizations are exploring ways AI systems can ...

Science in the modern era is increasingly reliant on enormous datasets and automated analysis. In astronomy, the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST)—a ten-year survey ...

Designed for insurers, asset managers, pension funds, and other long-term investors. In a world defined by volatility, persistent macro uncertainty and ever more complex investor objectives, ...

Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.