Millennials in their mid-thirties are less healthy than Generation Xers were at the same age, a recent analysis by Blue Cross Blue Shield found—a gap driven largely by poorer mental, cardiovascular and endocrine health outcomes in the younger generation.
CMS published its final rule to update the programs of all-inclusive care for the elderly (PACE), which provides comprehensive medical and social services to help keep elderly individuals who qualify for nursing homes in their homes longer.
A healthcare AI startup striving to become the biggest provider of virtual medicine in India has gotten a boost in the form of investor dollars and friendly coverage in a prominent business journal.
Physicians are burned out, and, left unchecked, those feelings of detachment from work come with a national cost of about $4.6 billion each year, according to new research published in the Annals of Internal Medicine.
Researchers have developed a deep-learning framework that can show how mutations in “noncoding DNA”—meaning parts of the strand that contain no genes—contribute to autism. And they believe their algorithm is generalizable for clinical researchers studying the role of noncoding mutations in just about any disease.
The U.K. is taking on a big pilot program with 500,000 people being remotely monitored at home using AI to analyze all the incoming data. The program by the National Health Service underscores where AI is likely to have the biggest impact in healthcare––non-consumption, or areas where there isn’t an affordable or convenient solution for consumers.
The Trump administration is expected to release an executive order this week that mandates the disclosure of healthcare prices across the industry, The Wall Street Journal reported. If enacted, the executive order could turn the traditionally opaque healthcare industry on its head.
A peer-reviewed journal has put out a call for papers to publish in an upcoming special issue on cutting-edge uses of AI in early-phase drug development.
Researchers in China have developed a deep learning algorithm able to diagnose hyperlipidemia—elevated levels of cholesterol, fats and triglycerides in the bloodstream—in both blood and urine specimens, potentially giving clinicians more information with less expense to the patient.
