The role of artificial intelligence in the fight against Covid-19

The role of artificial intelligence in the fight against Covid-19

In early January of 2020, the US Centers for Disease Control and Prevention issued its first warnings about the potential spread of a flu-like pandemic. Days later, the World Health Organization notified the public of the dangers of the novel coronavirus Covid-19, and warned about the possibility of a dangerous outbreak.

Despite the far-reaching resources of both the CDC and the WHO, a Canadian health start-up called BlueDot had already broken news of the threat to its users. It was able to do this using artificial intelligence and machine learning to spot patterns and track the spread of the virus.

BlueDot’s tracking system was the first of many AI-influenced technologies that are now being employed to fight the first global public health crisis of the decade. But aside from tracking, tracing, and predicting the spread of the virus, how are today’s modern smart cities leveraging AI to fight against Covid-19?

Thanks to the abundance of modern smart devices located across cities, from IoT connected sensors to wearable tech and communication devices, cities now collect more data than ever. Small data can be processed by humans, but big data requires machines to make use of it. And that’s where AI comes into play.

AI has been deployed across cities to help ease the damage caused by the Covid-19 pandemic. Diagnosing Covid-19 patients has been crucial in the first against the virus, and AI has played a leading role. Early on, it was assisting the detection of the virus using a deep learning tool that could identify the difference between Covid-19 and pneumonia using 2D and 3D modelling of CT scans.

By building on these models, doctors were able to learn more about the virus and track how it affects individual patients, and give researchers a better idea of the type of transmission and the scale of the spread of the virus. Early detection and diagnosis have been essential to preventing cities and other densely populated areas from being overwhelmed by the virus.

With early diagnosis and the ability to identify symptoms, cities have been able to harness the power of interconnected IoT networks, in partnership with other smart devices, from smart phones to smart bins, to help track, trace, and predict the potential spread of infection too.

Diagnosis is one thing, but actually alleviating the burden being placed on overcrowded hospitals has been an even bigger concern. Fortunately, AI has been able to step in and reduce that burden thanks to the introduction of AI triage systems that can automate medical processes and use the data supplied by patients to minimize the time that health professionals need to spend with individual patients. These triage systems have been able to classify patients depending on the severity and nature of their symptoms, allowing doctors and nurses to handle patients more effectively.

Telemedicine is another way that AI is being harnessed to reduce the burden on urban hospitals and provide better care to citizens in remoter regions. These intelligent platforms can be used reduce the need for unnecessary hospital trips, either by using consultation calls with real doctors, or via machine-learning enabled chatbots such as the CDC’s Clara service.

Similarly, AI has also been used to optimize the use of ventilator settings to ensure that patients are being administered oxygen correctly. Prolonged ventilator use can cause lung damage to patients but any ventilator that is being used longer than necessary deprives another patient of its use, particularly in small hospitals with limited resources.

The use of AI has evolved beyond the realm of data analysis and optimization. In some hospitals, AI-enabled healthcare robots have been used to perform a number of tasks, such as cleaning and disinfecting rooms, monitoring patients, and carrying out other routine tasks. According to some experts, AI-enabled robots will become more prevalent in crisis management in the future, too.

The rapid development of successful Covid-19 treatments and vaccines can also be attributed to the use of artificial intelligence. Vaccines often take years to develop, however, thanks to new ways of analysing data, Covid-19 vaccines were developed relatively quickly. The most significant tool used in the development of these vaccines was the Vaxign reverse vaccinology machine learning platform. By examining vast amounts of data about existing medications and vaccines, AI deep learning processes were able to identify potentially effective drug molecules and combinations, greatly expediting the vaccine production process.

As with many urban and smart city processes, the data required to enact many solutions already exists. However, it requires machine learning and artificial intelligence to adequately process it. By deep diving into vast data repositories filled with information about existing, approved, and validated drugs, the time required to develop new vaccines by a significant margin.

Trawling through data to find existing solutions to potential problems is what AI excels at. However, the recent pandemic has also forced governments to respond to an entirely new threat: the infodemic that has grown and spread with Covid-19. With populations more connected than ever before, and the delivery of information being freely available, tools that governments have relied on to raise awareness of societal issues have been used to spread harmful misinformation too.

To help counter this, governments and social media platforms have harnessed the power of AI and machine learning to curtail the spread of rumours and false information. Machine learning programmes have successfully been able to identify information from dubious origins and promote accurate and correct information instead.

On top of that, AI software can accurately identify and predict the threat level and danger of the virus by considering historical data and incorporating a wide range of factors. This accurate information has helped reduce panic and fear within cities, allowing governments and service workers to concentrate their efforts on tackling the virus rather than calming the population during this highly dynamic and changeable situation.

The global pandemic has sparked a greater appreciation for artificial intelligence technologies within cities. While it’s easy to feel mistrustful of AI-governed decision-making processes, the pandemic has highlighted their value and the need for modern cities to embrace data to find practical and efficient solutions to present-day and future challenges.

The current situation won’t usher in a blanket adoption of AI-enabled technologies, but it certainly helped to accelerate the trend towards embracing them.


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