How Big Data and AI have come to the aid of the healthcare industry in a pandemic.
Craig James Mundie, Senior Advisor to the CEO at Microsoft, believes data is so critical, it has become the new raw material of business. This is no exaggeration. The world is filled with devices that collect and transmit data. This is data in raw form, bits and bytes. A recent study estimated that currently, the Internet of Things (IOT) would have enough data to achieve 4.4 trillion gigabytes of data.
Gigabytes or such large groups of data, are culled as structured (from prepared sources like transactional information or user profiles), or as unstructured, (such as from social media archives emails or call centers and security cameras), or semi-structured. These groups of Big Data need to be processed and analyzed to transform them into valuable industry intelligence. The term big data was forged by technology expert, Roger Magoulas back in 2005, to describe massive, complex data sets almost impossible to manage and process with traditional data management tools. Yet, the world began noticing Big Data only around 2010.
Moreover, healthcare is an industry where entities produce data that results in global Big Data. While the global Big Data healthcare analytics market is currently worth over $22.6 billion, it is expected to be worth $34.27 billion by 2022, growing at an annual compound rate of 36% through 2025, by which time it could be worth $67.82 billion.
Big Data analytics in healthcare focuses on extraordinarily huge volumes of digital information culled from diverse sources such as patients’ Electronic Health Records (EHRs), medical imaging, genomic sequencing, payor records, pharmaceutical research, wearables and medical devices; the information collected is too large and complex to be handled by traditional technologies. Distinguished researcher in biomedical informatics, Atul J. Butte, said, Hiding within those mounds of data is knowledge that could change the life of a patient, or change the world. Indeed, Big Data helps to reduce healthcare costs for individuals, enhance treatment capacity of healthcare professionals, effectively avoid preventable diseases, predict outbreaks of epidemics or pandemics and improve overall quality of life.
Today, in the midst of a global pandemic, Big Data is a guiding light to scientists, epidemiologists and frontline health workers, enabling them to make informed decisions in their fight against Covid-19. Big Data helps them to continuously track the virus across the globe, using analytics to understand how the virus attacks, and to create effective vaccines to fight the pandemic.
In late March 2020, for instance, when the onset of Covid-19 was felt globally, Google Cloud said it would provide researchers across the world, free access to vital coronavirus information through its Covid-19 Public Dataset Program. This enabled free access globally, to Johns Hopkins Center for Systems Science and Engineering dashboard, Global Health Data from the World Bank, and OpenStreetMap data.
However, Big Data by itself as raw input, is unable to handle the swift responses needed to fight a global pandemic. As Alan Morrison, Senior Research Fellow at PriceWaterhouse Coopers, said, Big Data needs to be cleaned, structured and integrated to be useful, and is transformed into Artificial Intelligence (AI) as a result of processed data. For all that, Big Data and AI do work well together, as AI needs data to build its intelligence, especially, Machine Learning (ML). For instance, a ML image recognition app needs to view thousands of similar images from collected data, to be able to recognize a similar image in the future.
In the quest to monitor and control the global spread of Covid-19, the healthcare industry engaged Artificial Intelligence (AI) as a results-driven technology that can properly screen, analyze, predict and track current patients and likely future patients.
For instance, through algorithms and medical imaging technologies like CT scans and MRI scans, AI can recognize abnormal symptoms and other red flags that will alert healthcare authorities to possible Covid infection. Researchers like Joseph Paul Cohen at the University of Montreal, used lung images of Covid-19 patients to build an AI Covid-diagnosis system stemming from analysis of lung images. Thus, AI has helped develop a new diagnosis and patient management system for Covid-19 infection.
Furthermore, AI can construct an intelligent platform for automatic monitoring of Covid-19 and for providing daily updates of infected patients, while also predicting the probable spread of the infection.
With contact-tracing being a critical component of stemming the spread of Covid-19, AI is being used identify infected individuals and to help monitor them, through the contact-tracing process. In addition, AI can identify regions, countries and communities of the world most vulnerable to Covid-19, through available data, social media and other media platforms.
By analyzing available data on Covid-19, AI is used to research possible drugs that would be effective against the virus. AI can swiftly test drugs in real-time, where standard testing is lengthy and complicated. In fact, AI and network medicine have combined to assist in repurposing medications used for other challenging diseases, for emergency use in Covid-19.
AI, through algorithm-based detection, monitoring and diagnosis of Covid-19 patients, helps reduce the workload of exhausted frontline medical workers, overwhelmed by the sheer number of infected patients in hospitals.
Furthermore, by identifying the important characteristics of the pandemic, the probable causes for its arising, and the reasons for its spreading, AI is able to provide updated information on Covid to the medical industry. It will also be a baseline to fight other epidemics and pandemics in the future, indicating that AI will essentially play a vital role in providing more prognostic and preventive healthcare in the future.
As cardiologist, Ankala Subbarao, said, Processed data is information. Processed information is knowledge, Processed knowledge is Wisdom.
