I’m cautiously optimistic about artificial intelligence’s role in helping manage the coronavirus pandemic.

Google’s DeepMind unit, for example, is investigating deep-learning techniques for modeling the structure of the virus’ proteins, which could be useful in developing a vaccine. Meanwhile, the White House has asked researchers to develop machine-learning techniques to quickly analyze nearly 30,000 coronavirus-related studies to better understand the deadly virus.

Despite the number of promising projects, however, none of their A.I. is ready to be widely used today. It will likely take months or years more until the technology is ready to provide tangible results.

“I haven’t seen anything in which A.I. has helped us yet, clinically,” said Eric Topol, the founder and director of the nonprofit Scripps Research Translational Institute. He recently published the book Deep Medicine, which chronicles recent advances in A.I. and healthcare, among other topics. 

Topol is a big believer in A.I.’s increasingly important role in the medical industry. Using A.I. to mine drug databases and discover effective coronavirus (and other illnesses, for that matter) treatments could be helpful, but he has yet to see any specific technique that have advanced from research to a clinical setting.

Another promising area is using A.I. to crunch health-related data gathered from wearable devices like smartwatches or Internet-connected thermostats. Topol, for instance, mentioned the startup Kinsa Health, a seller of smart thermometers that has analyzed data from its products to identify the location of coronavirus hotspots in Florida. 

Topol’s own research team is conducting an A.I.-related coronavirus study based on heart rate data from smartwatches. Although his team doesn’t have enough data yet, he’s hopeful that once his team gets information, they can use A.I. techniques to find regions where people’s heart rates appear to be increasing during resting, a possible sign that they have fevers. That could ultimately show that Covid-19 is growing in a particular community, Topol explained.

“The analytics of that data is purely an A.I. story,” Topol said, explaining that his team will use neural networks—software that learns to identify patterns in huge quantities of data—to crunch the numbers. Because these studies rely on an immense amount of data, neural networks could be crucial to parsing all that information, he explained.

Whether his study will pan out is unclear. But whatever Topol and other researchers learn from their current A.I. studies won’t be for nothing because another pandemic may be around the corner. 

Jonathan Vanian