Abstract: Assessing children's learning in programming learning is important because the skills that children gain through programming learning are unknown. Additionally, the obtained learning effects ...

Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...

Machine learning has emerged as a transformative tool for the optimisation of biodiesel production, addressing the complexity and non-linearity inherent to feedstock ...

No system was recommended for individual prognostication, and the group considered that more detail in ulcer characterization was needed and that machine learning (ML)–based models may be the solution ...

Abstract: Over the past few years, machine learning has been responsible for the rapid advancements in fields such as computer vision, natural language processing and speech recognition. No small part ...

You're probably a little tired of reading or hearing about AI, right? Well, if that's the case, then you're in the right place because here, we're going to talk about machine learning (ML). Yes, it's ...

10 The George Institute for Global Health, School of Public Health, Imperial College London, London, UK Background Cardiovascular risk is underassessed in women. Many women undergo screening ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...