As the world witnesses the devastating toll of the SARS-CoV-2 disease, countries and businesses around the globe are all rushing to find the best cures and vaccines to this pandemic through innovations and technologies. In this trying time, AI has emerged as a major player in the medical race against the Covid-19 pandemic.
The Covid-19 pandemic has provided an opportunity for Artificial Intelligence (AI) to illustrate its potential in the medical field, particularly in the race to find treatments and vaccines. Over the last few months, AI has played various important supporting roles in this quest, including Data Mining, Contact Tracing, and even Virus Analysis, besides other usages. Here are the ways AI is contributing to the work and research against Covid-19.
1. Data Mining
Covid-19 research has quickly created unprecedented amounts of publicly available research data from federal governments, industry, and university research labs at record rates. As a result, scientists struggle to find the papers relevant to their specific research, to review the breadth of recent findings, and uncover insights. The first challenge is to collect the relevant literature and put it in a single, accessible location.
This is where AI came into help. The Covid-19 Open Research Dataset (CORD-19) created by the Allen Institute for AI in collaboration with government agencies, universities, and industry partners started with 13,000 Covid-19 scholarly articles. Two months later, it had grown to over 128 thousand articles. It’s updated daily as new research is published. This freely available data set is machine-readable, so researchers can create and apply natural-language processing algorithms, and hopefully accelerate the discovery of a vaccine.
2. Contact Tracing
AI has played a vital role in the Covid-19 outbreak since day 1. AI startup Bluedot detected a cluster of unusual pneumonia cases in Wuhan in late December and accurately predicted where the virus might spread. Robots have been reducing human interaction by disinfecting hospital rooms, moving food and supplies, and delivering telehealth consultations. AI is being used to track and map the spread of infection in real time, diagnose infections, predict mortality risk, and more. And the potential for future innovation cannot be overlooked.
As attention is focused on extracting knowledge from data related to the Covid-19 pandemic, privacy is top of mind. Developers are confronting privacy issues in a few ways. The contact tracing app DP-3T uses encrypted Bluetooth technology that allows smartphones to communicate anonymously with each other. Social contact information is then stored on individual devices rather than external servers to prevent widespread hacking. If someone tests positive for Covid-19, the people with whom they were in close contact with in prior days receive an alert with information on isolation and testing.
3. Virus Analysis and Treatment Development
In January, Google DeepMind introduced AlphaFold, a cutting-edge system that predicts the 3D structure of a protein based on its genetic sequence. In early March, the system was put to the test on Covid-19. DeepMind since then has released protein structure predictions of several under-studied proteins associated with SARS-CoV-2, the virus that causes Covid-19, to help the research community better understand the virus.
Many other teams of researchers have also joined forces, including The University of Texas at Austin and University of Washington’s Institute for Protein Design. This, in turn, requires considerable effort to keep up with the results emerging from labs around the world, raising the need for the analytic capabilities of AI. The most tantalizing prospect for automated analysis of the scientific literature is that AI will connect the dots between studies to identify hypotheses and suggest experiments, and even treatment, that would otherwise be missed.
The future from now
As we continue the fight against Covid-19, as well as battle ongoing complex societal and business challenges with AI, we will realize more of AI’s power once we learn how to integrate it into human teams with diversified expertise. In this regard, research is already showing promise in innovative ways. Humans can expect to add AI in their team as a new member, working in multiple fields alongside each other, in the coming future.
Sources: Wired.com, Forbes.com