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.  

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.

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.  

French researchers are designing an AI-based system to show diabetic patients their overall glycemic state in a readily understandable graphic display.

More than two-thirds of CV randomized clinical trial reports positively spin some aspect of the article to reflect favorable results that aren’t necessarily there, according to a study published in the May edition of JAMA Network Open.

The promised, less expensive insulin product from pharmaceutical company Eli Lilly has officially come to market, the company announced May 22.