Now they’re being clogged with AI slop. Scientific publishing has always had its plumbing problems. Even before ChatGPT, ...

Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...

A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

ABSTRACT: Postoperative nausea and vomiting (PONV) is a common complication after anesthesia and surgery. Traditional predictive models, such as Apfel scores, rely on linear assumptions and limited ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...

Abstract: With the increasing importance of digital security in the current world of finance, it is a must to find ways to implement artificial intelligence techniques to detect financial fraud ...

This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning. This ...