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

In the first instalment of LCGC International's interview series exploring how artificial intelligence (AI)/machine learning ...

A new review shows how AI helps food companies predict formulation, processing, and sensory outcomes. AI does not ...

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

Study uses artificial intelligence to analyze sleep-promoting effects of nearly 1,000 aromatic plants and recognize the ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Insulin resistance—when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels—is ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

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

When LambdaTest was founded, the problem it set out to solve was far more contained but with the rise of AI-generated code ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with ...