AI predicts 2.5B coronavirus infections

An AI simulation model predicts catastrophic effects of the novel coronavirus that originated in Wuhan, China, but the credibility of AI models is being called into question.

As many as 2.5 billion people could be infected with the disease within 45 days, with 52.9 million deaths, according to the simulation. Fintech startup founder of HedgeChatter, James Ross, built the AI simulation to estimate the global impact of the virus, prompted by another site that is tracking coronavirus globally.

As of publication, the virus has claimed 565 lives and infected more than 28,000. So far, Ross’ model has actually been accurate in predicting the following day’s publicly-released data within 3%, Forbes reported.

However, the model doesn’t account for every factor, including improvement in the reaction to the virus and conditions. In addition, the 2% mortality rate for coronavirus, which is extremely high and has prompted concern worldwide, could be wrong if some infected persons are asymptomatic. And it is unlikely to be as deadly as Ross’ AI model predicts.

See the full story below:

Amy Baxter

Amy joined TriMed Media as a Senior Writer for HealthExec after covering home care for three years. When not writing about all things healthcare, she fulfills her lifelong dream of becoming a pirate by sailing in regattas and enjoying rum. Fun fact: she sailed 333 miles across Lake Michigan in the Chicago Yacht Club "Race to Mackinac."

Around the web

The final list also included diabetes drugs sold by Boehringer Ingelheim and Merck. The first round of drug price negotiations reduced the Medicare prices for 10 popular drugs by up to 79%. 

HHS has thought through the ways AI can and should become an integral part of healthcare, human services and public health. Last Friday—possibly just days ahead of seating a new secretary—the agency released a detailed plan for getting there from here.

Philips is recalling the software associated with its Mobile Cardiac Outpatient Telemetry devices after certain high-risk ECG events were never routed to trained cardiology technicians as intended. The issue, which lasted for two years, has been linked to more than 100 injuries.