Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

Understanding how ozone behaves indoors is vital for assessing human health risks, as people spend most of their time inside.

This review systematically examines the integration of machine learning (ML) and artificial intelligence (AI) in nanomedicine ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Overview: Predictive models turn historical data into reliable forecasts that support accurate planning across ...

Maitri Mangal said she took AI courses daily and still spends hours every week learning about new AI-related material.

The AI’s learned behavior shows a clear preference for high-density, mixed-use development, increasing the spatial clustering ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using comprehensive health examination data from nearly 37 701 individuals.Methods ...

Discover how Ramkinker Singh's innovative dynamic scaling system revolutionises cloud security by intelligently managing ...

Traditional financial distress prediction relies heavily on backward-looking financial indicators such as leverage, liquidity ...