In this pandemic, scientists across the world are racing against time to find a cure or a vaccine for a virus that has taken thousands of lives and has infected millions across the globe. COVID-19, also known as Coronavirus, is spreading like a wildfire and has created a black swan event.

The black swan event, commonly used in the financial world is described as a negative occurrence of an event that is unexpected and difficult to predict.

COVID-19 has surely sent the markets reeling.

In response, the healthcare sector is turning to AI and related technologies to obtain and analyze data, automate work processes and get support in testing and detecting the disease.

Impact of AI in Medical and Healthcare Field

Artificial Intelligence tools are built on natural language processing and algorithms of machine learning, promising more valuable insights to the healthcare sector. From spotting the virus outbreak to measuring the disease’s economic impact,

AI is becoming more useful during this global catastrophe.

Coronavirus is testing the limitations of AI while AI technology is overcoming the problem of testing by decreasing the exposure of medical practitioners to the viruses by diagnosing patients, temperature detection, tracking the outbreak, providing assistance to medical staff, giving them more time to treat patients and streamlining the process of finding a cure. 

Making a Difference with AI

BlueDot, an AI platform company processes data in large quantities and tracks infectious diseases to predict and follow the spread of disease. This Canadian company was the first to identify, track and inform of the virus. Almost a week later, the World Health Organization declared the discovery of the novel coronavirus.

In such an uncontrollable situation of an outbreak, AI is helping track the disease spread and facilitating an early intervention. Using natural language processing and machine learning algorithms, AI can analyze the pattern of the spread of diseases, match symptoms with other similar scenarios and identify the best possible treatment for the disease.

AI and the Battle against COVID-19

While we provide AI unlimited access to information, it helps us parse data, learn from it, generate insights and come with predictions and possible outcomes. AI with its ability to combine data and patterns helps one to know the treatments or experiments that can be pursued.

Need for an on-demand healthcare app during the COVID-19 crisis

From diagnosing viruses to forecasting outbreaks to knowledge sharing to drug discovery, AI is used all over the world by different companies to help find cures by storing and correlating large amounts of data.

Testing Disease

Authorities in Spain and China have invested in robots to automate the testing of citizens for the Covid-19 and reduce medical practitioners’ exposure to the disease. Robots are able to check and diagnose quicker than humans.

Diagnosing Virus

An AI high tech company Infervision and Chinese e-commerce giant Alibaba have developed AI powered diagnosis systems that help medical practitioners detect and monitor the disease.

Drug Discovery

Drug discovery is a long and complex process that requires rigorous efforts to identify thousands of molecules and match them according to their use in various symptoms. AI accelerates the process in finding the right combination of the chemical and searching for the required drug as well as creating medicines.

How AI and Data Science can help in Coronavirus vaccine?

Medical Supplies

Drones are a blessing in disguise during these times. Drones have become the safest and fastest way of delivering medical supplies in areas with high demand. They are also helpful in patrolling public places, tracking patients and thermal imaging amongst providing other high tech support.

The Future

While AI is helping us fight the battle against COVID-19 and decelerate the spread of this disease, there is much bigger potential. And while the future of AI is definitely a bright one, we need vigilant and ethical guidelines to fill in the missing knowledge gaps.