Nature

An integrated physics-guided machine learning approach for predicting asphalt concrete fracture parameters

Accurate prediction of fracture energy (G f) in asphalt mixtures is important for durable asphalt pavements designing. Traditional experimental approaches are reliable but need resources, whereas ...
Nature

Interpretable machine learning model based on blood parameters for screening high myopia

To develop an interpretable machine learning (ML) model using routine blood parameters for high myopia (HM) screening as a convenient and cost-effective alternative to traditional methods. This ...

Even weak ocean models can provide valuable information for environmental forecasts, study shows

Oxygen depletion in the western Baltic Sea is not uncommon. Oxygen-poor conditions regularly occur in deeper waters, placing ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

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 ...
Semiconductor Engineering

AI Models Transform Defect Inspection And Review, But Can Fail To Scale

AI plays a role in improving defect capture rate and distinguishing between yield-killing and nuisance defects. New developments in wafer edge inspection are proving essential to bonded wafer yields.