The U.S. FDA has cleared the way for Physiq Inc., of Naperville, Ill., to market its continuous ambulatory respiratory rate algorithm, adding to the company's portfolio of cloud-based analytics for biopharma and health insurance companies. The 510(k) notification will allow Physiq to boost its higher-level artificial intelligence (AI) platform with validated vital signs inputs.

HONG KONG – Olive Healthcare Inc., a South Korean biotech startup, said its abdominal fat scanner Bello has received an FDA approval to sell the device in the U.S. The company said it plans to launch the scanner in the country this December, after a market test. The miniature device is portable with a weight of 3.8 oz (107 g), measuring 3.9 inches (10 centimeters) long, 3.1 inches wide and 1.9 inches high.

Deep learning algorithms developed at the Memorial Sloan Kettering Cancer Center (MSK) were able to distinguish prostate, skin and breast cancer with nearly perfect accuracy in a recent clinical trial. The technology has already been licensed exclusively by New York-based startup Paige.AI, which snapped up a $25 million series A early last year to continue to advance it.

Getting on top of the persistent HIV epidemic requires getting ahead of new cases, but only about 7% of at-risk patients have been advised of a prophylactic drug regime approved by the FDA seven years ago. Two new studies appearing in The Lancet HIV suggest that an algorithm that uses electronic health record (EHR) data can help physicians identify their at-risk patients who are good candidates for pre-exposure prophylaxis (PrEP), thus improving the odds that modern medicine might finally put an end to the scourge of acquired immunodeficiency syndrome.

A fast response with cardiopulmonary resuscitation (CPR) for cardiac arrest victims can save their lives, but older adults often are alone in their home or a bedroom when symptoms strike. Researchers at the University of Washington (UW) have developed a machine learning-based system that listens to ambient audio via dedicated smart speakers or smartphones for agonal breathing, the distinctive sound that a person in cardiac arrest makes.

NEW ORLEANS – The Apple Heart study has accumulated data from more than 400,000 participants in its evaluation of the ability of an algorithm to detect abnormalities that may be indicative of atrial fibrillation (AF), although the enrollment came up short of the target of half a million users. Nonetheless, Mintu Turakhia, a cardiologist at Stanford, Calif.-based Stanford University, said that while the study has some significant limitations, "we now have a footprint for evaluating technology such as this, and how to do this in an appropriate and scalable way."