Artificial Intelligence VS the Pandemic: Fighting COVID-19 Effectively

From contact tracing to predicting where the disease might spread next, artificial intelligence has been used extensively during the COVID-19 crisis. Traditional approaches to healthcare are often not effective enough when it came to fighting this disease on such a large scale, so healthcare organizations and government institutions turn to advanced technologies to try to mitigate the spread of COVID-19. Many successful use cases have proven that AI and healthcare can be a perfect match in the fight against the current coronavirus pandemic.

Artificial Intelligence For Clinical Trials

Tracing Сontacts and Finding the “Super Spreaders”

One of the most practical solutions of using AI and machine learning is tracing the contacts of people diagnosed with the virus. In many countries, health officials are able to identify carriers, who they had contact with, and even so-called “super spreaders” in time. This information allows them to take certain preventative measures, such as offering priority care to the most vulnerable patients, isolating those who are infected, and locking down high-contact areas, in addition to activating additional healthcare resources.

Using AI to Predict the Spread of Disease in Densely Populated Areas

AI can analyze large amounts of data and build predictive models based on this information. Officials in densely populated countries are able to estimate mortality rates, predict possible mutations, and allocate resources to specific areas before they are hit by the coronavirus. Using sophisticated, data-driven logistical models, supplies like PPE kits, oxygen cylinders, and vaccines can be delivered quickly to places where they are needed urgently.

By partnering with the AWS Diagnostic Development Initiative, many startups are providing insight into how the virus mutates and how many hospital beds and ventilation machines are needed, and even predicting the most effective amount of time to implement a lockdown.

Scaling and Adjusting to Provide an Adequate Response

Chatbots and other software powered by machine learning can help healthcare organizations effectively scale and adjust in times of crisis. Medical institutions use chatbots to help patients diagnose COVID symptoms without visiting a doctor in person. This helps reduce the risks of spreading the virus and allows patients with more severe symptoms to receive preferential treatment.

Other use cases involve creating chatbots to provide relevant and factual answers to people without placing an additional strain on healthcare institutions.

Providing Scientists with Up-to-Date Research

There is a lot of contradictory information about COVID-19. It can overwhelm healthcare providers, preventing them from doing their jobs effectively. To combat the problem of information overload, the medical community created an open research dataset called CORD-19, which contains almost 130,000 peer-reviewed research papers. Machine learning accesses the dataset and extracts relevant, precise information from unstructured scientific data to help researchers and healthcare providers get reliable answers to their questions about the pandemic.

Using Image Analysis to Detect Health Complications

Pneumonia is the most common coronavirus complication that can manifest in people of all ages. In some cases, it can turn deadly. Computer vision is one of the rapidly growing areas of machine learning that can recognize certain patterns in patients’ x-rays and improve the diagnostics of pneumonia. Even before the patients are tested for COVID-19, the medical imaging software can determine the appropriate level of care that a person needs.

Finding More Effective Types of Medicine

Artificial intelligence helps medical researchers find new treatments for COVID-19, and a similar process can be used to find antibiotics. Traditional, preliminary testing in a lab is slow and doesn’t work against resistant pathogens. Predictive models allow researchers to calculate and test thousands of new compounds with different concentrations and molecular structures in a virtual environment.

Using this method developed by scientists at MIT and IBM, researchers are now developing antiviral medicines. This automated screening process can create a list of potentially useful compounds, reducing the scope of research needed and speeding up the adoption of new medicines. Then those potential medicines can be tested in labs, on animals, and during clinical trials in humans to prove their effectiveness and applicability.

Reducing Panic and Vaccine Hesitancy with Chatbots

Fake news and misinformation are huge challenges that medical professionals have to face. Chatbots can be used to provide people with 24/7 access to proven, factual data that can help them make informed decisions about receiving medical treatment and, hopefully, reduce panic and vaccine hesitancy. Research out of France shows that people positively responded to the ease of use that chatbots provide and that they perceive them as unbiased and helpful tools. The hope is that these are some of the many AI tools that can reduce anxiety, improve attitudes towards vaccines, and, ultimately, stop the spread of COVID-19.