We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?

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 ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

The chapters of “Machine Learning Methods for Engineering Application Development“ book are organized into five parts Machine Learning Essentials, Applied Machine Learning, Surveillance Systems, ...

SAN FRANCISCO--(BUSINESS WIRE)--Herophilus, a leading biotechnology company developing neurotherapeutics to cure complex brain diseases, today announced the publication of research that describes a ...

Cosmic rays are high-energy particles that constantly bombard Earth from space and are influenced by the sun's magnetic activity. When the sun is active, fewer of these particles reach Earth; when the ...