The study departs from conventional mean-based economic forecasting by focusing on quantile prediction, a technique that ...

A comprehensive framework integrates statistical modeling, machine learning, and simulation to optimize urban traffic forecasting, capacity ...

A machine learning–driven web tool based on 13 standard patient metrics demonstrates strong predictive performance for MASLD, ...

Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...

Alvaro Sandroni is the E.D. Howard Professor in Political Economy at the Kellogg School of Management, Northwestern University, where he has taught since 1996. He received his PhD in economics in 1996 ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, ...

Understanding molecular diversity is fundamental to biomedical research and diagnostics, but existing analytical tools ...

Torgny Fornstedt describes how machine learning can work in practice for oligonucleotide analysis.

A machine learning model can use patient-reported data and remote therapeutic monitoring to accurately assess low disease ...