Statistical modeling continues to deliver distinct value to businesses both independent of, and in concert with, machine learning. “Artificial intelligence” (AI) and “machine learning” are ...

The Role of Assumptions in Statistical Model Selection is a critical topic in the field of statistics, ... Statistics versus machine learning. Nature Methods, 15(4), 233–234.

For its study, the research team set out to determine if a machine-learning statistical model could use health characteristics stored in electronic health records -- providing patient data such as ...

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.

Machine learning depends on a number of algorithms for turning a data set into a model. Which algorithm works best depends on the kind of problem you’re solving, the computing resources ...

Statistical risk models face issues of validity as unprecedented events and social phenomena occur. However, artificial intelligence (AI) and machine learning can assist models in maximising ...

Today’s data scientists and machine learning engineers now have a wide range of choices for how they build models to address the various patterns of AI for their particular needs.

Researchers have developed a machine learning model that could better measure baseball players' and teams' short- and long-term performance, compared to existing statistical analysis methods for ...