Artificial intelligence has played a central role in the fight against the coronavirus. Cotiviti has leveraged AI to predict COVID-19 hot spots around the country before an outbreak happens.
As the coronavirus continues to spread around the globe, we’ve seen a surge in the use of cutting edge technologies to track and control the pandemic, especially artificial intelligence. It seems like only a distant memory when artificial intelligence (AI) was being discussed as an emergent “existential threat” to humanity. However, with the rise of a pandemic, we’ve quickly embraced the ever-expanding capabilities of AI as a part of our first line of defense.
Recently, an AI platform fed mountains of pharmaceutical data and research studies journals determined that a rheumatoid arthritis medication could potentially be used to treat COVID-19 patients. As we reported earlier this month, some companies are deploying surveillance systems harnessing AI to pinpoint potential infections and mitigate the spread of the pandemic.
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One of the tremendous advantages of AI is the ability to absorb databases of information at warp speed. It’s simply too labor-intensive (if not virtually impossible) for a human being to review every single study and every clinical trial directly or indirectly related to a medical phenomenon.
“That’s how I spend my time between 2 o’clock in the morning and 4 o’clock in the morning, trying to catch up on a lot of the clinical information,” explained Dr. Emad Rizk, chairman, president and CEO of Cotiviti.
The healthcare analytics and solution company Cotiviti is now using AI and a mass of health data to predict future coronavirus hot spots around the US before these clusters emerge. During our interview, Rizk expressed his belief that AI and deep learning can greatly benefit mankind, from accelerating treatment to potentially improving current pharmaceuticals, but he does reiterate a sense of caution about the data being fed to the algorithms.
“You have to be careful that the algorithms are not using a small window of data. In other words, using just two to three data elements to come to a conclusion is a lot different than using 100 data elements,” Rizk said.
Predicting hot spots around the US
Cotiviti processes patient screening information and medical claims in its Caspian Insights Platform and uses this information to identify trends. The platform leverages machine learning alongside a wide spectrum of healthcare data to illustrate a “longitudinal” view of patient treatment and care outcomes over time.
The platform plays a central role in Cotiviti’s recently unveiled COVID-19 Outbreak Tracker. The interactive map provides weekly predictions about potentially hidden hot spots around the US. The map also highlights areas where coronavirus mitigation efforts may be working, illustrating a decreased probability of a hidden outbreak. Cotiviti uses a vast array of medical information including chest X-rays, emergency department visits, CPT codes, ICD-9 codes, and more to pinpoint hotbeds.
For more on mapping, check out our Flipboard magazine, Coronavirus maps
“We’re not looking at confirmed cases only, we’re looking at leading indicators by using o