The Department of Health and Human Services' health tech arm wants to hear from the healthcare industry about ways to speed up the adoption of artificial intelligence in medical treatment. | HHS wants ...

With the flood of data pouring in from across the healthcare industry there are still a lot of questions surrounding how best to make sense of said data, and where to store the heaps of new ...

Applying Machine Learning (ML) to physiological data poses several challenges. While ML can be effectively used to model well-defined systems, applying it to a system as complex as the human body ...

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 ...

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 ...

Social determinants of health and disease complexity were both key factors influencing gaps in care for congenital heart ...

The healthcare sector is increasingly reliant on digital technologies, demonstrating a strong commitment to using advanced tools for better patient care and more efficient data management. However, ...

2025 NOV 05 (NewsRx) -- By a News Reporter-Staff News Editor at Health Policy and Law Daily-- Data detailed on Machine Learning have been presented. According to news reporting from Hong Kong, ...

Balance training patients may soon be able to get AI feedback during home exercises, with four wearable sensors and a new ...