Artificial intelligence & Machine Learning are playing a key role in better understanding & addressing the COVID-19 crisis. Machine learning technology enables computers to mimic human intelligence and ingest large volumes of data and identify patterns and insights in short time. In the fight against COVID-19, organizations have been quick to apply their machine learning expertise in several areas: scaling customer communications, understanding how COVID-19 spreads, and speeding up research and treatment.
Enabling organizations to adapt to the new normal
Covid was unexpected blow to every organization in every possible way. Every small & large organization is finding new ways to operate effectively to meet the needs of their customers and employees as social distancing and quarantine measures remain in place. Machine learning technology is playing an important role in enabling that shift by providing the tools to support areas from remote communication, enable tel-medicine & to provide food security.
When every country of the world is trying to restructure & reboot AI and ML are playing a big role in helping companies. For healthcare institutions using machine learning-enabled chat-bots for contactless screening of COVID-19 symptoms and to answer questions from the public. One example is Covid chatbot to make it easier for people to find official government communications about COVID-19. Powered by real-time information from the government and the World Health Organization, the chatbot assesses known symptoms and answers questions about government policies. With almost 3 million messages sent to-date, this chatbot is able to answer questions on everything from exercise to an evaluation of COVID-19 risks, without further straining the resources of healthcare and government institutions. Many European countries like France are using the chatbot to decentralize the distribution of accurate, verified information.
Agriculture Solutions
Machine learning is also helping Agri-Tech & food supply chain. To avoid any disruption to the food supply chain, food processors and governments need to understand the current state of agriculture. Agri-Tech companies provide AI-driven crop-monitoring solution to retailers free of charge to provide additional resiliency and certainty to supply chains in the UK. The technology works to assess satellite images of crops to flag potential issues to farmers and retailers early on so they can better manage supply, procurement and inventory planning. The platform deploys custom machine learning models to mix imagery from multiple satellites, enabling a near real-time assessment of agricultural conditions. |
| Crop identification algorithm layered on top of satellite image. |
COVID-19 Research
Machine learning is helping researchers and practitioners analyze large volumes of data to forecast the spread of COVID-19, in order to act as an early warning system for future pandemics and to identify vulnerable populations. Researchers building models to estimate the number of COVID-19 infections that go undetected and the consequences for public health, analyzing 12 regions across the globe. Using machine learning and partnering with the Diagnostic Development Initiative, they have developed new methods to quantify undetected infections – analyzing how the virus mutates as it spreads through the population to infer how many transmissions have been missed.AI to detect disease outbreaks -
In Boston Children's Hospital web based application Heatmap uses artificial intelligence and data mining to spot disease outbreaks and issue location-specific alerts (colored dots) on COVID-19 and other diseases. It sounded an early alarm on the pandemic.At the beginning of this pandemic, BlueDot, a Canadian start-up that uses AI to detect disease outbreaks, was one of the first to raise the alarm about a worrisome outbreak of a respiratory illness in Wuhan, China. BlueDot uses AI to detect disease outbreaks. Using their machine learning algorithms, BlueDot sifts through news reports in 65 languages, along with airline data and animal disease networks to detect outbreaks and anticipate the dispersion of disease. Epidemiologists then review those results and verify that the conclusions make sense from a scientific standpoint. BlueDot provides those insights to public health officials, airlines and hospitals to help them anticipate and better manage risks.
Machine learning is helping leaders make more informed decisions in the face of COVID-19. In March, a group of volunteer professionals, led by former White House Chief Data Scientist DJ Patil, reached out to AWS for help supporting a scenario-planning tool that modeled the potential impact of COVID-19 in order to answer questions like: “How many hospital beds will we need?” or “For how long should we issue a shelter-in-place order?” They needed to scale their open-source model so governors across the US could understand the volume of exposure, infection and hospitalization to better inform their response plans. In close partnership with AWS and Johns Hopkins Bloomberg School of Public Health, the group moved the model to the cloud, allowing them to run multiple scenarios in just hours and to roll out the model to all 50 states and internationally to help with making decisions that directly impact the global spread of COVID-19.
Organizations are also examining ways to limit the spread of COVID-19, particularly among vulnerable populations. Closedloop, an AI start-up that we work with, is using their expertise in healthcare data to identify those at the highest risk of severe complications from COVID-19. Closedloop has developed and open-sourced a COVID vulnerability index, an AI-based predictive model that identifies people most at-risk of severe complications from COVID-19. This 'C-19 Index' is being used by healthcare systems, care management organizations and insurance companies to identify high-risk individuals, then calling them to share the importance of hand-washing and social distancing, and also offering to deliver food, toilet paper, and other essential supplies so they can stay at home.
