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

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

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.

The technology detects unique volatile organic compounds each mold species emits, creating distinct “odor signatures” the ...

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 ...

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” ...

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

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 ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

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