Artificial intelligence (AI) and data analytics are rapidly growing trends in the tech world. With increasing potential for innovation, it is paramount that we stay up to date with all the latest developments in this field. According to MarketsandMarkets, the worldwide artificial intelligence (AI) market will increase from USD 58.3 billion in 2021 to USD 309.6 billion by 2026, at a compound annual growth rate (CAGR) of 39.7 percent over the projected period. It seems that every company wants a piece of this growing pie. By 2022 it is expected that 90% of companies will be using some form of artificial intelligence for data analytics purposes.
COVID-19 is a pandemic that has swept the globe. Based on seroprevalence investigations, the United States is currently expected to have more than 6 million cases, with many more people thought to be exposed and asymptomatic. With the various COVID-19-related datasets that have been collected, AI is assisting us in fighting this virus through applications such as early detection and diagnosis, contact tracing, case and death projections, medication and vaccine research, and so on.
What are AI and Data Analytics?
Artificial intelligence (AI) is a broad term that defines machines capable of human-like functions. Specifically, it refers to the ability of an application to be able to solve problems on its own. In other words, AI allows computers to learn and perform tasks without direct instructions from users. Perceptual computing is one of the most important fields in artificial intelligence research. It deals with computer vision, which is commonly defined as the ability of a computer. Artificial intelligence is the theory and development of computer systems capable of performing activities normally requiring human intelligence.
Data analytics is a process by which large amounts of data are analyzed to reveal patterns, trends, and associations, especially relating to human behavior and interactions. In increasingly automated work environments, artificial intelligence has become a crucial tool for companies looking to streamline their processes and cut costs. Data analytics is the ability to find insights from data and make informed decisions based on that. AI technology is used in data analytics to help us understand these insights faster and make smarter decisions.
The COVID-19 Pandemic: How It Will Reinforce The Need for AI and Data in 2022
In 2022, Artificial intelligence and big data will be the driving force in the growth of humanity and the economy. One of the major factors that will accelerate this is the emergence of artificial intelligence and big data. Data analytics is not just a trending topic. In fact, it is one of the most important trends in the future. Artificial intelligence will be a major part of the future and will be used to control and improve every industry.
While advanced AI applications in healthcare hold great promise, we currently lack the large datasets and accuracy of data required to go beyond fairly simple algorithms and truly improve outcomes. AI, at its most basic level, is the process of teaching machines to behave like humans, automating tasks like coding claims and scheduling appointments. AI is most commonly used in healthcare today to automate tasks like call center routing and appointment scheduling.
There are at least two reasons why we don’t have the necessary data sets to fulfill AI’s promise in healthcare. For starters, much of our healthcare data is siloed between providers’ offices, health insurers’ offices, laboratories, and other locations. Each location collects patient data, but the data sets do not communicate with one another. Second, much of what influences health occurs outside of healthcare settings, in places where patients live, work, and play.
The good news is that activity in this field is brisk. COVID-19 compelled us to digitize healthcare interactions, and federal regulations require that datasets adhere to standards that enable integration. These trends point to exponential growth in the size and granularity of our datasets, allowing healthcare data scientists to begin training the models required to fully realize AI’s potential to impact clinical outcomes.
The Primary Contributions of AI-based Data Analytics in COVID
Artificial intelligence and other cutting-edge technologies used to combat the pandemic aided in early detection and diagnosis, trend analysis, intervention planning, healthcare burden forecasting, comorbidity analysis, and mitigation and control. Some contributions of AI-based data-driven analytics in COVID are:
- AI impacted the COVID-19 era in six distinct ways, including epidemic containment strategies (ECS), epidemic data life cycle (EDLC), epidemic handling with heterogeneous source data (EHHSD), healthcare-specific AI (HCSAI) services, general epidemic AI services (GEAIS), and drug design and repurposing (DDAR) against COVID-19, which have not been covered in the recent literature
- The difficulties in applying AI to available epidemic data that is not in desirable form at the moment due to a variety of issues (e.g., diverse formats, legislation, heterogeneous sources, and privacy concerns, among others).
- It elaborates on the privacy issues that arise as a result of the ongoing pandemic’s movement of person-specific data in cyberspace.
- It provides a concise overview of the most recent technologies, other than AI, that have contributed to the fight against the recent pandemic through innovative features.
- It discusses numerous cutting-edge studies that have used AI techniques for good in the ongoing COVID-19 pandemic.
Conclusion – Why You Can’t Afford To Ignore The Power of AI and Data Analytics
COVID-19 has many complex clinical implications for people who have underlying diseases like diabetes, pneumonia, and heart disease, to name a few. As a result, we may need to use AI and data analytics to deal with the clinical implications of COVID-19’s prognosis. To summarize, Data Analytics and AI are the business of the future. As a result, if you want to help your business, you should consider adopting these cutting-edge technologies. Now, whether you are a business owner or a service provider, you must be well-versed in technologies before implementing them.
This article was originally published on Hackernoon and is reproduced with permission.
