Reviewed by Margaret JamesFact checked by Jared EckerReviewed by Margaret JamesFact checked by Jared Ecker Predictive modeling uses known results to create, process, and validate a model to forecast ...

Geisinger and IBM this week announced this week that they've co-created a new predictive model to help clinicians flag sepsis risk using data from the integrated health system's electronic health ...

A new technique able to forecast how changes to parameters will impact biomanufacturing processes could revolutionize drug production, save manufacturers time and money, and help increase access to ...

To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.

Dr. Michael Spaeder of the University of Virginia previews his upcoming HIMSS26 talk on using AI and machine learning to detect potentially catastrophic health events.

Everyone wants predictive algorithms to be accurate, but there are different ways to define accuracy. Is it better to have an algorithm that's rarely perfect, but also rarely off by a mile? Or to have ...

CMS, the Office of Inspector General and other governmental agencies have ramped up their stance on healthcare fraud and abuse, estimating that roughly $4.1 billion in taxpayer money was recovered in ...

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...