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 ...

One of the shared, fundamental goals of most chemistry researchers is the need to predict a molecule's properties, such as its boiling or melting point. Once researchers can pinpoint that prediction, ...

Deep learning, a multifaceted and groundbreaking subset of Artificial Intelligence (AI), is reshaping various sectors, ...

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

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 ...

Among hospitalized patients with cirrhosis, a machine learning (ML) model enhanced mortality prediction compared with traditional methods and was consistent across country income levels in a large ...

Chronic kidney disease (CKD) is a complex condition marked by a gradual decline in kidney function, which can ultimately ...

Overview Clear prompts help machine learning models become more accurate and reliable.Role-specific prompts generate focused ...

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...