Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...

Heat stress is widely recognized as a critical risk factor in livestock systems. Rising temperatures and humidity levels can ...

Strong predictive signals don't automatically translate into investable strategies, especially at institutional scale.

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

New deep-learning framework reconstructs hourly PM2.5 chemical composition using air-quality and meteorological data ...