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 ...

As rapidly growing amounts of data are created and used in industry and research environments, there is an increasing demand for people who are able to pursue data-driven thinking and decision-making ...

LifeTracer, a computational framework, was developed to analyze mass spectrometry data, identifying molecular features that distinguish abiotic from biotic origins. Georgia Tech and NASA used advanced ...

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

Railway infrastructure could be made safer and more reliable using AI, artificial intelligence, according to research ...

A new computer tool based on machine learning allows for quicker identification of previously unknown molecules in natural extracts. Based on decision theory, it learns to "think" like an expert ...

A NIMS research team has developed a new experimental method capable of rapidly evaluating numerous material compositions by ...

Even as machine learning and artificial intelligence are drawing substantial attention in health care, overzealousness for these technologies has created an environment in which other critical aspects ...