As society grapples with the pandemic challenge trying to find a cure, businesses, on the other hand, are struggling to realign themselves to reality with the aid of technology.
Big data, artificial intelligence, and machine learning are proving to be allies to epidemiologists, joining hands with data scientists to fight the COVID-19 crisis.
Most likely, the pandemic attack has presumably brought AI and big data analytics in the forefront, with organizations and healthcare sectors from across the globe thriving to find ways to curb the virus from spreading.
New measures introduced using new technologies
The spread of coronavirus has sparked the significance of using machine learning, artificial intelligence, data science, and big data analytics to gain a solid understanding of the virus. Ever since the pandemic attacked the US, scientists and researchers have been working closely to uncover the indescribable nature of the virus, the severity of it attacks from individual to individual, and the possible measure one can take to help reduce the spread. At the core of all these effects and activities happening across the globe: there is one factor the industry is aware of – data.
James Hendler, the Tetherless World Professor of Computer, Web, and Cognitive Science at Rensselaer Polytechnic Institute (RPI) and director of the Rensselaer Institute for Data Exploration and Applications (IDEA), made a statement to the Health IT Analytics saying, “this is, in essence, a big data problem. We’re trying to track the spread of disease around the world.”
Researchers at RPI are extensively using big data analytics to examine the virus from every point of view. This institute announced saying they would soon allow research organizations and research entities to have the privilege of accessing innovative tools to further help combat the pandemic.
Here’s how data science and big data analytics are helping us through the crisis:
Foresee the unseen
Data extracted from trusted sources led to extensive information sharing via messages and visualizations to educate the public about the virus. Visualizations are a good option to teach the public how to avoid getting infected and what are the preventive measures we can follow to stop the virus from spreading. Due to the democratization of data and analytic tools in combination with the ability to share messages through the internet allowing us to witness the ability of how people can use data. In present times, many organizations have bought pandemic data in-house for them to develop their proprietary intelligence. Other companies have set up an internal track and respond command centers to help their employees, customers, and a broader ecosystem via the current situation.
Off late HCL realized they would be needing its command center dedicated solely for COVID-19 response coordinated by the senior management. Doing so provides autonomy to the HCL data scientists to develop creative and relevant insights to make informed decisions. For instance, developing predictive analytics that causes a huge impact on HCLs customers and the market they serve.
Crafting the right response
Healthcare administrators at Sheba Medical Center in Israel have started using data-driven forecasting to straighten out the allocation of resources well in advance before the outbreak starts. These solutions were likely possible with the help of machine learning algorithms that provides better insights based on the data extracted – confirmed deaths, confirmed cases, population density, migration flow, demographics, availability of medical resources, medical supplies, pharma stockpiles, and contact tracing, etc.
With the help of the data extracted and the right analytical tools, we can further answer questions like, where will the next cluster likely to arise or which demographic is likely to be affected by the virus and how will the virus mutate within a different timeframe.
Diagnose, treat and cure
BlueDot, an AI system operated by a Toronto-based startup was the first to detect the earliest anomalies relating to the pneumonia strain that took place in Wuhan during December 2019. The AI system assessed more than one million articles in 65 different languages that further helped detect a similar incident during the SARS outbreak in 2003. It was only nine days after which WHO alerted the public about the emergence of this new virus attack.
Developing healthcare solutions is still challenging, this is where AI comes to play. The AI technology is already working on the COVID-19 outbreak by helping diagnose the virus using imaging analysis, decreasing diagnosing time used to be carried out through a CT scan from 5 minutes to merely 20 seconds. With the help of automation, AI has not only helped reduce the rising diagnostic workload but has also freed up valuable resources to help focus more on treating the affected patients.
As the world is still embracing the impact of the ongoing pandemic crisis, we must realize that technology like big data analytics, AI, and machine learning are tools of cumulative innovation of humanity. And that with time, we will have the required tools and technologies to fight against the virus attack within the next coming weeks and months.
With the right technology pointed out in the right direction, we have the potential to curb and minimize the impact of COVID-19.