Researchers at National University of Singapore used multiple interpretable machine learning methods to predict traffic congestion in in Alameda ...

In AIoT-based systems, sensors continuously collect high-frequency data such as vibration, temperature, pressure, and electrical signals. These data streams are processed by machine learning and deep ...

The study points up interpretability as a critical barrier to trust and adoption. Many AI-based cybersecurity tools function ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Arguments against the state using biometrics bounce back and forth, but sometimes the job of government is not just to ...

Acute respiratory distress syndrome (ARDS) remains a major challenge in critical care, with mortality rates often exceeding 35–40%. Mechanical ...

In 2025, traders leverage on-chain metrics, AI-driven sentiment analysis, and specialized indices to monitor real-time crypto market emotions ...

Cell-line development enhances biopharmaceutical production capacity and quality, but complex biologics like bsAbs and ADCs ...

Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to ...

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