Smartwatches are among the wearable devices that gather health data. Translating that data into useful information can be complicated and expensive. (iStock) The human body constantly generates a ...

Big data, machine learning, and interoperability are all topics we’ve been hearing about for many years in health tech. But in fact these banner ideas are deeply intertwined with one another. Machine ...

The Operationalization Gap. It’s the chasm between innovation and everyday practice that is a challenge for all large organizations. Hospital executives will likely not be surprised to learn that the ...

Increasing surgical services revenue is a top priority for most health systems, but reliance on manual operating room scheduling and operational inefficiencies can impede these efforts. Often, poor ...

Strive Health, a value-based kidney care provider, noticed many of its health IT vendors, like the provider itself, operate extensively in the value-based care space and collaborate with accountable ...

Using infrared light and machine learning, researchers have developed a method to effectively screen human health and its deviations at a population level. Envision a scenario where a single drop of ...

Seventy-five percent of U.S. health systems are now using at least one artificial intelligence application, up from 59% in 2025, a new survey from Eliciting Insights found. The go-to market research ...

Metabolite data and AI combine to redefine how we measure aging and predict health spans. Study: Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning ...

MEDABLE Inc., a leading application and analytics platform for healthcare, announced Cerebrum, the first cloud-based machine learning solution created specifically for healthcare apps. Cerebrum ...