Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

Fault Detection and Classification Market is projected to hit USD 12.7 bn by 2033, driven by a robust CAGR of 9.3% over the ...

Learn how data fabric addresses fragmentation, compliance, and Shadow IT to deliver robust, centralized data protection and ...

Zero-trust architecture is essential for modern defense and aerospace operations, offering layered security, real-time responsiveness, and flexible integration.

The researchers believe the appeal of ML formats is because many security tools do not yet support robust detection of embedded malicious behavior within such files. “Security tools are at a primitive ...

Developing classification models based on brain EC using machine learning and deep learning techniques has become a cutting-edge approach for identifying and diagnosing neurodegenerative diseases.

The best performance model had an AUC of 90% (95% CI, 75% to 100%) and it was built with just five lncRNA. 25 However, validation of those models in an independent data set, the Oncology Research ...

This study evaluates the predictive performance of three machine learning models—Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)—for classifying CHD. The models were ...

Machine Learning for Morphological Galaxy Classification The "Machine learning for morphological galaxy classification" is a repository for classifying Galaxy Zoo 2 (GZ2) images into (1) Galaxy and ...

Anomaly detection in network traffic is a critical aspect of network security, particularly in defending against the increasing sophistication of cyber threats. This study investigates the application ...

This study introduces an innovative computational approach using hybrid machine learning models to predict toxicity across eight critical end points: cardiac toxicity, inhalation toxicity, dermal ...