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

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

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...

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

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

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

What Are Non-Human Identities in Cybersecurity? Non-Human Identities (NHIs) might sound like a concept from a science fiction novel, but they are a crucial component. These unique “machine identities” ...

How Does Machine Identity Security Foster Confidence in Cybersecurity? Is your organization truly equipped to handle the complexities of machine identity security? While we navigate a rich with ...

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 ...

According to the authors, incorporating a broad spectrum of biomarkers allows the models to reflect the continuous and ...

Acute systemic inflammation has long been suspected to trigger harmful processes within the brain, contributing to ...