Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...

The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...

Feasibility and Acceptability of Collecting Passive Smartphone Data for Potential Use in Digital Phenotyping Among Family Caregivers and Patients With Advanced Cancer This study applied three ...

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.

What if the programming language you rely on most is on the brink of a transformation? For millions of developers worldwide, Python is not just a tool, it’s a cornerstone of their craft, powering ...

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

Background: Acute ST-segment elevation myocardial infarction (STEMI) is a cardiovascular emergency that is associated with a high risk of death. In this study, we developed explainable machine ...