TMCnet

Machine Learning Advances in Predictive Cyber Threat Detection

Cyber threats are increasing in speed and complexity, driving the need for advanced detection techniques. Machine learning is ...
Devdiscourse

High-accuracy AI models improve IoT threat detection

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...
EurekAlert!

Attention detection using EEG signals and machine learning: A review

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...

PanGIA Biotech Non-Invasive Cancer Detection Abstracts Accepted for Presentation at AACR Annual Meeting 2026

PanGIA Biotech, Inc. ("PanGIA Biotech" or "Company") announced that two research abstracts have been accepted for ...

PanGIA Biotech Announces Peer-Reviewed Study in Diagnostics Showing 97.8% Sensitivity in Detecting Prostate Cancer Using a Urine-Based Liquid Biopsy with Machine Learning

PanGIA Biotech, Inc. ("PanGIA") announced a peer-reviewed clinical study published in Diagnostics, "Urine-Based Machine Learning Assay Detects Prostate Cancer," (1) demonstrating clinical validation ...
Frontiers

AI & Machine Learning in the Diagnosis and Care of Head and Neck Cancers

Head and neck cancers represent a biologically heterogeneous group of malignancies requiring accurate diagnosis, staging, and risk stratification for ...