As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Earlier this year, the Carnegie Classification of Institutions of Higher Education came out with a new classification, focused on colleges’ low-income student enrollments and whether their students ...

ABSTRACT: Predicting knowledge of tuberculosis (TB) could imply several significant changes in the management, control and prevention of this disease. These would be based on advanced technological ...

Spontaneous regression of cancer is an uncommon event observed most often in neuroblastoma, leukemia, lung cancer, and melanoma. The underlying mechanisms are not fully understood; however, infections ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Abstract: The recent development of advanced data analytics and machine learning promoted the introduction of diverse learning techniques designed to alleviate challenges related to two major ...

📖 Project Overview This repository implements One-vs-Rest (OvR) and One-vs-One (OvO) strategies for multi-class classification, focusing on selecting the most important features to improve model ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...

When Donald Trump stormed into the White House in 2016, horrified Americans debated, almost endlessly, whether the shocking result was an expression of widespread racism (backlash to a Black president ...

Frailty assessment in patients with advanced/metastatic renal cell carcinoma using routine data collected during treatment with tyrosine kinase inhibitors in the STAR trial. ML analysis results: ...

Abstract: Linear regression and its variants have achieved considerable success in image classification. However, those methods still encounter two challenges when dealing with hyperspectral image ...