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 ...

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 advancements in machine learning have ushered in a transformative era for seismic data analysis. By integrating sophisticated algorithms such as convolutional neural networks (CNNs), generative ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Organizations no longer need to rely on traditional methods of data analysis to extract valuable insights. With the emergence of artificial intelligence (AI) tools, repetitive tasks that take too much ...

Our eLibrary offers over 25,000 IMF publications in multiple formats. This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML ...

For the first time, researchers have used machine learning – a type of artificial intelligence (AI) – to identify the most important drivers of cancer survival in nearly all the countries in the world ...

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...