The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale. By integrating daily ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale.

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...

Young, T. , Guymon, J. , Pankow, M. and Ngaile, G. (2026) A Material Removal Prediction Framework for Ball EEM Polishing in ...

Harvard University is offering free online courses for learners in artificial intelligence, data science, and programming.

Abstract: Urban vegetation classification is challenging due to the heterogeneous nature of urban environments. Accurate mapping of urban vegetation, which plays a crucial role in regulating ...

Abstract: The purpose of this study is to estimate and predict onion wholesale price volatility using statistical and machine learning algorithms. Traditional models like ARIMA and GARCH were compared ...

A new study by Justin Grandinetti of the University of North Carolina at Charlotte challenges one of the most dominant narratives in artificial intelligence: that modern AI systems are inherently ...

Federal scientists announced a new artificial intelligence tool that can forecast drought conditions 90 days ahead across the entire United States, marking a significant step in how the government ...

Ischemic heart failure (IHF) is a major cause of cardiovascular morbidity worldwide, characterized by complex tissue remodeling and inflammation. However, reliable molecular biomarkers for early ...