GitHub

Sibghatullah-pk/Log-Analysis-Using-Machine-Learning

Evaluation (one-liner): This is a fully-functional network log analysis and threat detection system combining rule-based threat classification, intelligent session grouping, machine learning ...
Computer Weekly

Glasgow researchers use machine learning to build network digital twin

Researchers at the University of Glasgow have developed a new way to test networks, which they claim is 25,000 times faster than traditional approaches. Shenjia Ding, a research student at the ...
IEEE

A Comprehensive Survey on Cognitive Cyber Security Analysis Using Machine Learning Approaches

Abstract: Cybersecurity threats have evolved in sophistication, necessitating the development of intelligent and adaptive defense mechanisms. Cognitive cybersecurity systems present the opportunity to ...
Phys.org

Machine learning accelerates analysis of fusion materials

Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in fusion reactors, but the ultra-high heat can damage its microscopic ...
techtimes

AI Cyberattacks Rising: How Hackers Use Machine Learning to Launch Smarter Attacks

AI cyberattacks are rapidly transforming the cybersecurity landscape, enabling attackers to automate and scale operations with unprecedented speed. Through machine learning hacking, adversaries can ...
IEEE

Wastewater Attributes Analysis using Machine Learning

This research addresses the critical challenge of inefficient wastewater management by developing machine learning-driven predictive models for real-time analysis. Traditional wastewater analysis, ...
The Lancet

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

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
Journal of Medical Internet Research

Machine Learning Prediction Models for Preeclampsia: Systematic Review and Meta-Analysis

Background: Preeclampsia is a severe hypertensive disorder with rising global prevalence. While machine learning (ML) models for predicting preeclampsia are increasingly published, existing evidence ...
acm.org

Integrating Machine Learning into Physical Security Architecture

Recent advancements in the field of artificial intelligence (AI) have exposed many modern organizations to the benefits of intelligent automation. According to research published by McKinsey, almost ...
Phys.org

Machine learning automates material analysis and design using X-ray spectroscopy data

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy (XAS) is an important technique for this, as it reveals detailed insights ...
Frontiers

Integrated bioinformatic analysis and machine learning developed a prognostic model based ...

The disease burden of acute myeloid leukemia (AML) continues to pose a significant public health challenge globally. Mitochondria play a critical role in tumor development and progression by ...