Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...

To help professionals build these capabilities, we have curated a list of the best applied AI and data science courses.

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a table. Instead of chemical elements, the new chart arranges learning ...

This special report introduces small area estimation (SAE) as a modern approach for producing reliable, stand-level forest inventory information Small area estimation (SAE) is a set of statistical ...

Abstract: Malware poses a significant threat to network and information system security, particularly in industrial Internet of Things (IIoT) environments, where embedded systems and edge devices ...

Advanced fraud detection system using machine learning to identify fraudulent transactions and activities. This project implements multiple machine learning algorithms including Random Forest, XGBoost ...

One of the key issues faced by financial institutions is the prediction of loan default. Two machine learning methods, Random Forest and K-Nearest Neighbors (KNN), are tested in this study, using an ...

ABSTRACT: Atrial fibrillation (AF) is a leading cardiac arrhythmia associated with elevated mortality risk, particularly in low-resource settings where early risk stratification remains challenging.

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...