How AI and machine learning are helping to fight COVID-19

robots

(Owen Beard, Unsplash)

This article is brought to you thanks to the collaboration of The European Sting with the World Economic Forum.

Author: Emma Charlton, Senior Writer, Formative Content


  • Organizations have been quick to apply their AI and machine learning know-how in the fight to curb this pandemic.
  • These technologies are being deployed in areas from research to healthcare and even agriculture.

As the world grapples with COVID-19, every ounce of technological innovation and ingenuity harnessed to fight this pandemic brings us one step closer to overcoming it. Artificial intelligence (AI) and machine learning are playing a key role in better understanding and addressing the COVID-19 crisis. Machine learning technology enables computers to mimic human intelligence and ingest large volumes of data to quickly identify patterns and insights.

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 scale and adjust

Every kind of organization, whether small or large, public or private, is finding new ways to operate effectively and 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 remote communication, enable telemedicine, and protect food security.

For healthcare and government institutions, that includes using machine learning-enabled chatbots for contactless screening of COVID-19 symptoms and to answer questions from the public. One example is Clevy.io, a French start-up and AWS customer, which has launched a chatbot to make it easier for people to find official government communications about COVID-19. Powered by real-time information from the French 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. French cities including Strasbourg, Orléans and Nanterre are using the chatbot to decentralize the distribution of accurate, verified information.

To avoid any disruption to the food supply chain, food processors and governments need to understand the current state of agriculture. Agri-tech start-up Mantle Labs, another AWS customer, is offering its cutting-edge AI-driven crop-monitoring solution to retailers free of charge for a period of three months 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.

Health, pandemics, epidemics

What is the World Economic Forum doing about fighting pandemics?

The first human trial of a COVID-19 vaccine was administered this week.

CEPI, launched at the World Economic Forum, provided funding support for the Phase 1 study. The organization this week announced their seventh COVID-19 vaccine project in the fight against the pandemic.

The Coalition for Epidemic Preparedness Innovations (CEPI) was launched in 2017 at the Forum’s Annual Meeting – bringing together experts from government, business, health, academia and civil society to accelerate the development of vaccines against emerging infectious diseases and to enable access to these vaccines during outbreaks.

Coalitions like CEPI are made possible through public-private partnerships. The World Economic Forum is the trusted global platform for stakeholder engagement, bringing together a range of multistakeholders from business, government and civil society to improve the state of the world.

Organizations can partner with the Forum to contribute to global health solutions. Contact us to find out how.

Understanding how COVID-19 spreads

Machine learning is also 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 at the Chan Zuckerberg Biohub in California have built a model 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 AWS 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.

At the beginning of this pandemic, BlueDot, a Canadian start-up and AWS customer 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 modelled 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. Closed Loop 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 handwashing and social distancing, and also offering to deliver food, toilet paper, and other essential supplies so they can stay at home.

Speeding up research and treatment

Healthcare providers and researchers are faced with an exponentially increasing volume of information about COVID-19, which makes it difficult to derive insights that can inform treatment. In response, AWS launched CORD-19 Search, a new search website powered by machine learning, that can help researchers quickly and easily search for research papers and documents and answer questions like “When is the salivary viral load highest for COVID-19?”

Built on the Allen Institute for AI’s CORD-19 open research dataset of more than 128,000 research papers and other materials, this machine learning solution can extract relevant medical information from unstructured text and delivers robust natural-language query capabilities, helping to accelerate the pace of discovery.

In the field of medical imaging, meanwhile, researchers are using machine learning to help recognize patterns in images, enhancing the ability of radiologists to indicate the probability of disease and diagnose it earlier.

UC San Diego Health has engineered a new method to diagnose pneumonia earlier, a condition associated with severe COVID-19. This early detection helps doctors quickly triage patients to the appropriate level of care even before a COVID-19 diagnosis is confirmed. Trained with 22,000 notations by human radiologists, the machine learning algorithm overlays x-rays with colour-coded maps that indicate pneumonia probability. With credits donated from the AWS Diagnostic Development Initiative, these methods have now been deployed to every chest x-ray and CT scan throughout UC San Diego Health in a clinical research study.

Machine learning can also help accelerate the discovery of drugs to help treat COVID-19. BenevolentAI, a UK AI company and AWS customer, turned its platform toward understanding the body’s response to the coronavirus. They launched an investigation using their AI drug discovery platform to identify approved drugs which could potentially inhibit the progression of the novel coronavirus. They used machine learning to help derive contextual relationships between genes, diseases and drugs, leading to the proposal of a small number of drug compounds. In just days, BenevolentAI found that Baricitinib (a drug currently approved for rheumatoid arthritis, owned by Eli Lilly) proved the strongest candidate. Baricitinib is now in late-stage clinical trials with the US National Institute for Allergies and Infectious Diseases (NIAID) to investigate its efficacy and safety as a potential treatment for COVID-19 patients. The speed with which the drug entered clinical trials reflects the urgency of the global pandemic and the significance of AI in facilitating the discovery of new treatments.

I’m inspired and encouraged by the speed at which these organizations are applying machine learning to address COVID-19. I have always believed in the potential of machine learning to help solve the biggest challenges in our world – and that promise is now coming to fruition as organizations respond to this crisis. It is my hope that in this difficult time we can work together on a global scale to innovate and find new ways machine learning can contribute in the fight against COVID-19.

the sting Milestone

Featured Stings

Can we feed everyone without unleashing disaster? Read on

These campaigners want to give a quarter of the UK back to nature

How to build a more resilient and inclusive global system

Stopping antimicrobial resistance would cost just USD 2 per person a year

Migration has set EU’s political clock ticking; the stagnating economy cannot help it and Turkey doesn’t cooperate

South Asia can become an innovation hub. Here’s how

Why a global recession isn’t inevitable

What does artificial intelligence do in medicine?

The benefits of a cashless society

Japan must urgently address long-standing concerns over foreign bribery enforcement

Coronavirus: Commission proposes to activate fiscal framework’s general escape clause to respond to pandemic

A Valentine’s Special: giving back, a dialogue of love

If on a summer’s night: is UK businesses’ “new deal” the only key to the “best of all worlds”?

World Retail Congress Dubai 2016: Retail’s night of nights

Virus Coronavirus: No time to die

Chart of the day: This is what violence does to a nation’s GDP

Palestine refugees’ relief chief warns Security Council money to fund Gaza operations will run out in mid-June

Africa-Europe Alliance: Four new financial guarantees worth €216 million signed under the EU External Investment Plan

European Junior Enterprises to address the significant skills mismatch in the EU between school and employment

What happiness can teach us about how we measure human development

Celebrities are helping the UK’s schoolchildren learn during lockdown

Taking fast road to ‘e-mobility’ central to a sustainable future: COP24

US-China trade war is a ‘lose-lose’ situation for them and the world, warn UN economists

This digital currency could build a more sustainable global economy

UN relief chief urges Security Council to back aid delivery, more funding for millions of Syrians hit by harsh weather

EU to finance new investment projects with extra borrowing; French and Italian deficits to be tolerated

Could the fourth wave of globalization help to end epidemics?

EU adopts rebalancing measures in reaction to US steel and aluminium tariffs

UN chief welcomes start of Church-mediated national dialogue in Nicaragua

It’s time for global businesses to accept local responsibility

WHO working to save lives following powerful earthquake in Albania

Parliament demands ban on neo-fascist and neo-Nazi groups in the EU

We won’t win the online security war without people power

Grave concern over escalating humanitarian crisis, casualties, displacement across northwest Syria: UN

Banks can fight financial crime. But we can’t do it alone

China-EU Summit on 16-17 July 2018: “Work together to address common challenges”, by China’s Ambassador to the EU

Juncker Plan exceeds original €315 billion investment target

Rising inequality affecting more than two-thirds of the globe, but it’s not inevitable: new UN report

25 years on from genocide against the Tutsi, UN Chief warns of ‘dangerous trends of rising xenophobia, racism and intolerance’

How cities, not states, can solve the world’s biggest problems

Mergers: Commission prohibits proposed merger between Tata Steel and ThyssenKrupp

Microplastics have been found in Rocky Mountain rainwater

Mali: Two peacekeepers dead after dawn attack, several injured – UN Mission

Russia and the West to partition Ukraine?

RescEU: MEPs vote to upgrade EU civil protection capacity

Professional practices of primary health care for Brazilian health and gender inequality

Universities need strategic leadership. Here’s what it looks like

The health of the human being in coexistence with a transformative biosphere

Voices of Afghan women ‘must be heard at the table in the peace process and beyond’ UN deputy chief tells Security Council

Managing and resolving conflicts in a politically inclined group of team members

Telemedicine and the Brazilian reality

UN’s Grandi slams ‘toxic language of politics’ aimed at refugees, migrants

G20 to Germany: Abandon miser policies

German elections: Is Merkel losing ground or Shultz is winning?

EU paves the way for a stronger, more ambitious partnership with Africa

‘An unprecedented fiscal response’ – political and business leaders on managing the coronavirus crisis

Urgent action needed to address growing opioid crisis

I have a rare disease. This is my hope for the future of medicine

Bill Gates’ top 10 breakthrough technologies of 2019

Eurobarometer: protecting human rights tops citizens’ list of EU values

Global aid appeal targets more than 93 million most in need next year

Help prevent children ‘from becoming victims in the first place’, implores Guterres at campaign launch

Don’t let the virus quarantine your mind –Ways to strengthen “Mental” immunity

The developing countries keep the world going

More Stings?

Advertising

Trackbacks

  1. […] How AI and machine learning are helping to fight COVID-19 […]

Speak your Mind Here

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s