Europe and the world are grappling with the coronavirus pandemic that has claimed more than 70,500 lives and infected at least 1.2 million patients, according to the John Hopkins University coronavirus map.
These numbers are changing daily. While the focus is on slowing down the spread of the novel respiratory virus first identified in Wuhan, China, there are legitimate questions about AI’s role in detecting, preventing, and managing the pandemic.
AI and COVID-19 pandemic.
The outbreak of the SARS coronavirus (SARS-CoV) in southern China between November 2002 and July 2003 resulted in 774 deaths from 8,098 official cases. The outbreak was contained before it could reach many parts of the world. However, it managed to reach other Asian nations, Europe, and North and South America. The SARS-CoV outbreak reminded the world that this was not the end of disease outbreaks or pandemics, but rather a warning that this could become a constantly recurring feature on the health calendar. And there have been a few more outbreaks, mainly epidemics.
And nearly 17 years later, we are faced with the SARS-CoV-2, the main cause of the coronavirus pandemic. Have we learned anything from the SARS-CoV outbreak, or at least, do we have advanced technologies to better detect, track, and prevent devastating effects of this new pandemic? But the technological landscape has changed. Can AI, alongside machine learning, natural language processing (NLP), and robotics be called upon to detect, prevent, and manage pandemics?
Bluedot, a Canadian startup used an AI-based algorithm to warn people against traveling to China due to the possibility of a flu-like outbreak. The startup, which uses data analytics to predict the spreading of infectious diseases, rang the warning bells before the World Health Organization and the Centers for Disease Control and Prevention (CDC) gave their warnings.
In Europe, the epicenter of the coronavirus pandemic has moved to Italy, where more than 5,000 deaths have been recorded. The virus is spreading to new regions where its effects might be worse, with Italy being a good example. High-resolution population density maps can be used to predict how and where the virus will spread. AI tools such as facial recognition and temperature detection software can be employed to identify people who may be infected by the disease. China developed a monitoring system that uses big data to predict a person’s chances of being infected with the virus based on factors such as their travel history, exposure to potential COVID-19 patients, and more.
An AI-powered cure, vaccine, or treatment.
An important step toward the development of a cure for diseases such as COVID-19 is a clinical trial. A clinical trial is the research or tests done on people. Recruitment of the ‘right people’ in clinical studies is slow, time-consuming, and expensive. This should not be the case during the pandemic when time is everything. Natural language processing (NLP), a subcategory of AI, allows researchers to identify patients eligible to participate in clinical trials. NLP relies on algorithms that analyze medical reports written by doctors to identify the right people for trials.
Machine learning, harnessed with the ‘right’ computing power, is used to understand the structure of the virus and present the results to researchers to develop vaccines or treatments. MIT researchers used machine learning to identify an antibiotic that can be used to fight against disease-causing bacteria. While the development of new drugs takes long, predictive analytics can be applied to go through the list of existing drugs and propose which might be useful to manage the pandemic.
Robotics play an important role in minimizing the spread of the disease while protecting frontline workers from harm’s way. Robots have been deployed to aid in delivering food and medical supplies and cleaning and testing quarantine facilities to reduce the transmission of the disease from patients to healthcare workers.
The spread of the pandemic has led to the rise in misinformation especially on social media platforms. Chatbots can be used to separate facts from myths.
Building a firewall against new infections.
It is possible to use AI to build a huge firewall to safeguard us against new infections? This requires the ability to predict new infections, identify symptoms in patients, track patients, detect new high-risk areas, and use AI in fast-tracking the development of the new medication. Is AI ready to save us from the next health crises? Maybe not. But there is hope that it could mitigate the effects of pandemics.
By: Michael Jurgen Garbade
Source: Entrepreneur Europe
January is a month CIOs often use to look back on the past year to build plans for the next. 2020 was a year like no other, and when Data Executives reflect on the “tech-celeration” their company experienced, they could find it challenging to prioritize opportunities for 2021 and beyond.
From more reusable packaging to more companies taking back used products to more empowered designers, 2021 will be a key year in the development of new, less wasteful systems.
As we enter this new year, I thought it would be helpful to see what people from a full century ago envisioned for us. Newspapers of 1921 were full of predictions—some right, and some very wrong.