Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...

Browser-based attacks hit 95% of enterprises — and traditional security tools never saw them coming

Omdia research shows 95% of organizations faced browser-based attacks last year. CrowdStrike's CTO and Clearwater Analytics' ...
Semiconductor Engineering

Semiconductor Supply Chain Security Using Side-Channel Power Measurements and Generative Adversarial Networks (Cornell)

Band Power Side-Channel Detection for Semiconductor Supply Chain Integrity at Scale” was published by researchers at Cornell ...
SecurityWeek

Cyber Insights 2026: Threat Hunting in an Age of Automation and AI

Understanding how threat hunting differs from reactive security provides a deeper understanding of the role, while hinting at how it will evolve in the future.
IEEE

Detection of Valvular Heart Diseases From PCG Signals Using Machine and Deep Learning Models: A Review

Abstract: Artificial intelligence (AI) predictions are widely used to address challenges in the heart health sector, such as providing clinical decision support. Early detection of valvular heart ...
Tech Xplore on MSN

Detection of concealed explosives using terahertz spectral imaging and deep learning

Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current ...

New Android malware uses AI to click on hidden browser ads

A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact ...
Tech Xplore

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
Compliance WeekOpinion

How banks are responsibly embedding machine learning and GenAI into AML surveillance

As financial crime grows in scale, speed, and sophistication, banks are increasingly turning to artificial intelligence, ...
IEEE

Enhanced Predictive Modeling for Anomaly Detection in Financial Transactions Using Machine Learning

Abstract: Credit card fraud detection presents a significant challenge due to the extreme class imbalance in transaction datasets. Traditional machine learning models struggle to achieve high recall ...