1. Demand Prediction Engine: A Technological Leap from "Passive Response" to "Active Anticipation" ...

Results Machine learning models trained on tabular data exhibit a 76% accuracy for the random forest model at predicting relapse evaluated with a 10-fold cross-validation (the model was trained 10 ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

To predict the formability of these kinds of glasses, Yale researchers have developed a machine learning model based on 201 alloy features constructed from the combination of 31 elemental features, ...

This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML prediction results relative to traditional econometric approaches, explores non ...

A new machine learning approach developed through an international collaboration between Polytechnic University of Milan and Drexel University could help architects and urban planners better predict ...

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in ...

They're using machine learning to fully analyze a patient's tumour, to better predict cancer progression. Researchers analyzed two sets of MRIs from each of five anonymous patients suffering from GBM.

Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...