If not the most deadly, the novel coronavirus (COVID-19) is one of the most contagious diseases to have hit our green planet in the past decades. In little over three months since the virus was first spotted in mainland China, it has spread to more than 90 countries, infected more than 185,000 people, and taken more than 3,500 lives.
As governments and health organizations scramble to contain the spread of coronavirus, they need all the help they can get, including from artificial intelligence. Though current AI technologies are far from replicating human intelligence, they are proving to be very helpful in tracking the outbreak, diagnosing patients, disinfecting areas, and speeding up the process of finding a cure for COVID-19.
Data science and machine learning might be two of the most effective weapons we have in the fight against the coronavirus outbreak.
Tracking the coronavirus outbreak with machine learning
Just before the turn of the year, BlueDot, an artificial intelligence platform that tracks infectious diseases around the world, flagged a cluster of “unusual pneumonia” cases happening around a market in Wuhan, China. Nine days later, the World Health Organization (WHO) released a statement declaring the discovery of a “novel coronavirus” in a hospitalized person with pneumonia in Wuhan.
BlueDot uses natural language processing and machine learning algorithms to peruse information from hundreds of sources for early signs of infectious epidemics. The AI looks at statements from health organizations, commercial flights, livestock health reports, climate data from satellites, and news reports. With so much data being generated on coronavirus every day, the AI algorithms can help home in on the bits that can provide pertinent information on the spread of the virus. It can also find important correlations between data points, such as the movement patterns of the people who are living in the areas most affected by the virus.
The company also employs dozens of experts who specialize in a range of disciplines including geographic information systems, spatial analytics, data visualization, computer sciences, as well as medical experts in clinical infectious diseases, travel and tropical medicine, and public health. The experts review the information that has been flagged by the AI and send out reports on their findings.
Combined with the assistance of human experts, BlueDot’s AI can not only predict the start of an epidemic, but also forecast how it will spread. In the case of COVID-19, the AI successfully identified the cities where the virus would be transferred to after it surfaced in Wuhan. Machine learning algorithms studying travel patterns were able to predict where the people who had contracted coronavirus were likely to travel.
Using computer vision to detect coronavirus infection
You have probably seen the COVID-19 screenings at border crossings and airports. Health officers use thermometer guns and visually check travelers for signs of fever, coughing, and breathing difficulties.
Now, computer vision algorithms can perform the same at large scale. An AI system developed by Chinese tech giant Baidu uses cameras equipped with computer vision and infrared sensors to predict people’s temperatures in public areas. The system can screen up to 200 people per minute and detect their temperature within a range of 0.5 degrees Celsius. The AI flags anyone who has a temperature above 37.3 degrees. The technology is now in use in Beijing’s Qinghe Railway Station.
Alibaba, another Chinese tech giant, has developed an AI system that can detect coronavirus in chest CT scans. According to the researchers who developed the system, the AI has a 96-percent accuracy. The AI was trained on data from 5,000 coronavirus cases and can perform the test in 20 seconds as opposed to the 15 minutes it takes a human expert to diagnose patients. It can also tell the difference between coronavirus and ordinary viral pneumonia. The algorithm can give a boost to the medical centers that are already under a lot of pressure to screen patients for COVID-19 infection. The system is reportedly being adopted in 100 hospitals in China.
A separate AI developed by researchers from Renmin Hospital of Wuhan University, Wuhan EndoAngel Medical Technology Company, and the China University of Geosciences purportedly shows 95-percent accuracy on detecting COVID-19 in chest CT scans. The system is a deep learning algorithm trained on 45,000 anonymized CT scans. According to a preprint paper published on medRxiv, the AI’s performance is comparable to expert radiologists.
Robots at the frontlines of the fight against COVID-19
One of the main ways to prevent the spread of the novel coronavirus is to reduce contact between infected patients and people who have not contracted the virus. To this end, several companies and organizations have engaged in efforts to automate some of the procedures that previously required health workers and medical staff to interact with patients.
Chinese firms are using drones and robots to perform contactless delivery and to spray disinfectants in public areas to minimize the risk of cross-infection. Other robots are checking people for fever and other COVID-19 symptoms and dispensing free hand sanitizer foam and gel.
Inside hospitals, robots are delivering food and medicine to patients and disinfecting their rooms to obviate the need for the presence of nurses. Other robots are busy cooking rice without human supervision, reducing the number of staff required to run the facility.
In Seattle, doctors used a robot to communicate with and treat patients remotely to minimize exposure of medical staff to infected people.
AI is speeding up drug research
At the end of the day, the war on the novel coronavirus is not over until we develop a vaccine that can immunize everyone against the virus. But developing new drugs and medicine is a very lengthy and costly process. It can cost more than a billion dollars and take up to 12 years. That’s the kind of timeframe we don’t have as the virus continues to spread at an accelerating pace.
Fortunately, AI can help speed up the process. DeepMind, the AI research lab acquired by Google in 2014, recently declared that it has used deep learning to find new information about the structure of proteins associated with COVID-19. This is a process that could have taken many more months.
Understanding protein structures can provide important clues to the coronavirus vaccine formula. DeepMind is one of several organizations who are engaged in the race to unlock the coronavirus vaccine. It has leveraged the result of decades of machine learning progress as well as research on protein folding.
“It’s important to note that our structure prediction system is still in development and we can’t be certain of the accuracy of the structures we are providing, although we are confident that the system is more accurate than our earlier CASP13 system,” DeepMind’s researchers wrote on the AI lab’s website. “We confirmed that our system provided an accurate prediction for the experimentally determined SARS-CoV-2 spike protein structure shared in the Protein Data Bank, and this gave us confidence that our model predictions on other proteins may be useful.”
Although it’s too early to tell whether we’re headed in the right direction, the efforts are commendable. Every day saved in finding the coronavirus vaccine can save hundreds—or thousands—of lives.
This story is republished from TechTalks, the blog that explores how technology is solving problems… and creating new ones. Like them on Facebook here and follow them down here:
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