In recent times, there has been a lot of discussion of artificial intelligence in public forums, some generated by thought leaders like Bill Gates and Stephen Hawking. Late last year Hawking actually argued that artificial intelligence “could spell the end of the human race.”
But most scientists and researchers don’t seem to be as worried as Gates and Hawking. They contend that while machines and software may do an increasingly better job of imitating human intelligence, there’s no foreseeable way in which they could become a self-conscious threat to humanity.
In fact, it seems far more likely that AI will work to serve human needs, including healthcare improvement. Here’s five examples of how AI could help bring us smarter medicine (courtesy of Fast Company):
- Diagnosing disease:
Want to improve diagnostic accuracy? Companies like Enlitic may help. Enlitic is studying massive numbers of medical images to help radiologists pick up small details like tiny fractures and tumors.
- Medication management
Here’s a twist on traditional med management strategies. The AiCure app is leveraging a smartphone webcam, in tandem with AI technology, to learn whether patients are adhering to their prescription regimen.
- Virtual clinicians
Though it may sound daring, a few healthcare leaders are considering giving no-humans-involved health advice a try. Some are turning to startup Sense.ly, which offers a virtual nurse, Molly. The Sense.ly interface uses machine learning to help care for chronically-ill patients between doctor’s visits.
- Drug creation:
AI may soon speed up the development of pharmaceutical drugs. Vendors in this field include Atomwise, whose technology leverages supercomputers to dig up therapies for database of molecular structures, and Berg Health, which studies data on why some people survive diseases.
- Precision medicine:
Working as part of a broader effort seeking targeted diagnoses and treatments for individuals, startup Deep Genomics is wrangling huge data sets of genetic information in an effort to find mutations and linkages to disease.
In addition to all of these clinically-oriented efforts, which seem quite promising in and of themselves, it seems clear that there are endless ways in which computing firepower, big data and AI could come together to help healthcare business operations.
Just to name the first applications that popped into my head, consider the impact AI could have on patient scheduling, particularly in high-volume hostile environments. What about using such technology to do a better job of predicting what approaches work best for collecting patient balances, and even to execute those efforts is sophisticated way?
And of course, there are countless other ways in which AI could help providers leverage clinical data in real time. Sure, EMR vendors are already rolling out technology attempting to help hospitals target emergent conditions (such as sepsis), but what if AI logic could go beyond condition-specific modules to proactively predicting a much broader range of problems?
The truth is, I don’t claim to have a specific expertise in AI, so my guesses on what applications makes sense are no better than any other observer’s. On the other hand, though, if anyone reading this has cool stories to tell about what they’re doing with AI technology I’d love to hear them.
