IEEE

Intrusion Detection in IoT and IIoT: Comparing Lightweight Machine Learning Techniques Using TON_IoT, WUSTL-IIOT-2021, and EdgeIIoTset Datasets

Abstract: The security of Internet of Things (IoT) and Industrial Internet of Things (IIoT) systems has been significantly enhanced through the integration of effective intrusion detection systems ...
IEEE

A Review on Quantum Machine Learning in Applied Systems and Engineering

Abstract: Quantum Machine Learning (QML) has emerged as a promising frontier within artificial intelligence, offering enhanced data-driven modeling through quantum-augmented representation, ...
Nature

How AI slop is causing a crisis in computer science

Large language models (LLMs) can suggest hypotheses, write code and draft papers, and AI agents are automating parts of the research process. Although this can accelerate science, it also makes it ...

AI model may predict when MND patients need feeding tubes within months

A new AI tool that accurately predicts the need for a feeding tube could transform patient care and improve quality of life ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Journal of Medical Internet Research

Development and Validation of a Web-Based Machine Learning Model for Predicting Early Neurological Deterioration Following Stroke Thrombolysis: Multicenter Study

We systematically evaluated 27 clinical parameters using multiple machine learning algorithms to develop ENDRAS, a prediction model based on six readily available clinical variables. Model performance ...