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

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

A research team led by Professor Takuya Yamamoto and Assistant Professor Ryusaku Matsumoto (Department of Life Science Frontiers) has developed a machine learning model that enables early prediction ...

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 ...

This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest ...

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 ...

A research team led by Professor Takuya Yamamoto and Assistant Professor Ryusaku Matsumoto (Department of Life Science Frontiers) has developed a machine learning model that enables early prediction ...

SportsLine's Machine Learning Model AI reveals the top Week 2 NFL props, best bets and SGP for the Week 2 NFL schedule on ...