Artificial intelligence brings to classification a scalable, accurate alternative. Using natural language processing and ...

The 2025 SANS SOC Survey shows AI use is rising, but many SOCs lack integration, customization, and clear validation ...

In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its ...

The technology detects unique volatile organic compounds each mold species emits, creating distinct “odor signatures” the sensors can recognize 30-minute detection: The device analyzes air samples in ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Dr. McBain studies policies and technologies that serve vulnerable populations. On any given night, countless teenagers confide in artificial intelligence chatbots — sharing their loneliness, anxiety ...

Abstract: Advancements in machine learning (ML) have facilitated the prediction of key aspects of human locomotion, particularly in identifying subject gait trajectories essential for recognizing ...

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...