Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

Fraud detection is defined by a structural imbalance that has long challenged data-driven systems. Fraudulent transactions typically account for a fraction of a percent of total transaction volume, ...

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...

Researchers developed a blood test that spots ALS with 90% accuracy. The 46-gene panel could cut diagnostic delays that now ...

Agenda-driven opinion mills, designed more to sway public opinion than serve the public, might be harder to spot if AI is used to make them sound more original and rational. So the race is on to stay ...

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

For Gabriel Petersson, the path to becoming a research scientist at OpenAI didn’t start in a lecture hall but began with a ...

The new HER2DX central nervous system (CNS) progression score predicts risk of brain progression in advanced HER2+ breast cancer, addressing a major unmet need in identifying patients at the highest ...

Researchers at the University of South Australia are using machine learning for hyperspectral imaging to detect contamination ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...