In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Recent progress in survival analysis has been driven by the integration of machine learning techniques with traditional statistical models, such as the Cox proportional hazards model. This synthesis ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

For more than 20 years in experimental particle physics and astrophysics, machine learning has been accelerating the pace of science, helping scientists tackle problems of greater and greater ...

Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...

Overview: AI in financial services uses machine learning and automation to analyze data in real time, improving speed, accuracy, and decision-making across bank ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Combining microscopy and machine-learning techniques leads to faster, more precise analyses of critical coating materials ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...