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 ...
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 ...
Devdiscourse

Quantum vs classical AI: Traditional models still lead in phishing detection

Quantum machine learning is being explored as the next frontier in cybersecurity, but new research shows it remains far from replacing established artificial intelligence systems in detecting phishing ...
InvestorsHub on MSN

Broadcom introduces AI-driven fraud detection tool for payment authentication

Broadcom Inc. (NASDAQ:AVGO) has launched Arcot Smart Ruleset, a machine learning–based fraud detection platform designed to ...
TMCnet

Sigma360 and Consilient Announce Strategic Integration to Transform Financial Crime Detection with Federated Machine Learning Driven pKYC and Transaction Risk Monitoring

A New Standard for Financial Integrity As financial crime and regulatory scrutiny intensify, the industry is moving beyond static, periodic reviews to continuous risk assessment. The Sigma360 and ...

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 ...
European Medical Journal

Multicancer Detection Achieved with Single Blood Test

New cfDNA test enables multicancer detection with high accuracy, offering a cost effective approach for early diagnosis and screening.
News-Medical.Net

Machine learning model predicts liver cancer risk with high accuracy

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient's risk of hepatocellular carcinoma (HCC), the most common ...