Previous methods struggle to incorporate real-time data or account for nonlinear interactions among macroeconomic variables. This leaves a critical gap in anticipating fiscal stress events. Machine ...

Techniques such as Raman spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), and ...

A Comparative Study of AI-Powered Chatbot for Health Care. Journal of Computer and Communications, 13, 48-66. doi: 10.4236/jcc.2025.137003 . The need for this research arises from the increasing ...

While artificial intelligence (AI) holds promise to improve the diagnosis of melanoma, researchers of a new review outlined ...

University of the Philippines researchers have developed AI models to predict E. coli's antimicrobial resistance using ...

AI's role in predictive analytics for energy savings helps Smart Cities manage resources more efficiently, say experts ...

Metric learning has significantly improved machine learning applications such as face re-identification and image classification using K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) ...

Semisupervised scheme has emerged as a popular strategy in the machine learning community due to the expensiveness of getting enough labeled data. In this paper, a semisupervised incremental support ...

However, with its use case directly addressing Bitcoin’s pitfalls, coupled with bullish expectations for Bitcoin and the cryptocurrency market over the coming ...

FAYETTEVILLE, GA, UNITED STATES, July 1, 2025 /EINPresswire.com/ -- A sweeping new review reveals how satellites are helping scientists track a quiet but widespread shift in global agriculture: the ...

We break down new meme coins to watch now, like Simon’s Cat, Build on BNB, and Tutorial. Learn how they compare in ...

"These models were chosen to compare performance across different learning strategies and to identify which ... Forest (RF), which is well-suited for high-dimensional data; Support Vector Machine (SVM ...