Predictive modeling is a method prevalent across a wide swath of industries, from insurance to manufacturing to genetic research.

In the 17th century, German astronomer Johannes Kepler figured out the laws of motion that made it possible to accurately ...

The AI models, paired with standardized care pathways, can be transformative in addressing readmissions and other high-impact ...

As predictive models learn from examples, training a model aiming to support the differentiation between patients suffering from major depressive disorder and individuals with bipolar disorder ...

Traditional AI models learn from structured data and are optimized for outcomes like classification, forecasting or ...

Predictive modeling is used in banking to identify fraud and illegal activities. For example, the amount and frequency of transactions are analyzed to recognize patterns or trends in money laundering.

Predictive analytics can support organizations in minimizing and even preventing damage. For example, predictive models can pinpoint trends that indicate potential risks.

Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain–behavior relationships from connectivity data using cross-validation.

But most models only either explain or predict: they don’t do both. In the investment industry, people commonly confuse an explanatory model with a predictive one. This can be an expensive mistake.