Hot Topic: Trending AI DIAGNOSTICS news from the past few weeks

AI is stepping in to help speed up the diagnosis of COVID-19 and expedite how much time healthcare professionals spend determining COVID-19 pneumonia and non-COVID-19 cases.

It may be time to take a long last look at the vision exam that relies on a cardboard sheet of huge letters at the top and tiny ones at the bottom.

Johns Hopkins radiologists have repurposed a deep learning algorithm designed to detect tuberculosis on chest x-rays to, instead, help identify COVID-19.

The European Union has certified AI software for reading mammograms, clearing the way for a South Korea-based AI vendor to sell another of its AI products across the European Economic Area.

It was late April when the CDC added impaired taste and/or smell to its list of COVID-19 symptoms. Thanks to AI and natural language processing (NLP), researchers at the Medical University of South Carolina had beaten the federal agency to the punch.

Notching its fifth go-ahead from the FDA, an Israel-based AI startup has received the agency’s 510(k) clearance to market software that automatically identifies signs of compression fractures in the spine.

An experimental set of algorithms has achieved accuracy of 70% to 80% at predicting which of 53 COVID-positive patients at two hospitals in China would get the sickest.

Researchers in the U.K. and U.S. have developed an automatic prediction model that can tell if someone is infected with COVID-19 based on symptoms alone.

AI developers working to refine COVID-19 detection in chest x-rays must navigate two unavoidable speed bumps.

The FDA has cleared an investor-backed teleradiology provider to market two AI algorithms the company developed to flag certain stroke-associated findings in images from head CT scans.