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.

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 ...

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

For far too long, two specters have been haunting the world of artificial intelligence and warfare, and they both featured 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 ...

AIQuant Labs has launched DexTrader.ai, a machine learning-powered investment platform designed to bring institutional-grade ...

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

Data quality and interoperability become critical enablers. Agentic systems rely on timely, accurate information from across ...

Combining microscopy and machine-learning techniques leads to faster, more precise analyses of critical coating materials ...