The way we live our lives and carry out our daily tasks has altered dramatically since the first few months of 2020. The COVID-19 epidemic has expedited the adoption of Artificial Intelligence (AI) in various industries, even though widespread use of future robot taxis and self-driving commercial vehicles has yet to become a reality. We’ve seen the equivalent of many years’ worth of digital revolution happen in just a few months. The impact of these advancements has been very immediate, whether in tracing epidemiological peaks or conducting contactless payments, a window has opened up on what’s to come.

Here, we examine and debate how artificial intelligence (AI) can assist us in combating the ongoing pandemic. Clinical studies and human abilities are still essential, despite AI’s vast and unquestionable benefits. Although diverse approaches and methods have been created in different countries, the fight against the pandemic appears to have found a beneficial partner in AI, a global and open-source tool capable of assisting in this health disaster. We would be able to work in this complex scenario including healthcare, society, and research with the help of applying AI carefully.

AI may be used to create an intelligent platform for autonomous viral monitoring and prediction. A neural network can be created to extract the visual aspects of this condition, which would aid in the proper monitoring and treatment of those who are affected. It can provide daily information on patients as well as options for dealing with the COVID-19 epidemic. AI can assist in analyzing the virus’s level of infection, identifying clusters and “hot spots,” as well as successfully tracking and monitoring individual contacts. It can also help forecast the disease’s future course and the likelihood of recurrence.

AI can provide updated knowledge that is useful in the prevention of the spread of the pandemic through real-time data analysis. During this crisis, it can be utilized to estimate the likely sites of infection, the virus’s invasion, and the need for beds and healthcare experts. With the use of prior mentored data over data prominent at different times, AI can help prevent future virus and disease outbreaks. It identifies the characteristics, causes, and motivations for infection dissemination. In the future, this technology will be crucial in the fight against other epidemics and pandemics. It can be used as a preventative strategy as well as a treatment for a variety of other disorders.

“Population health,” as the name implies, focuses on cohorts rather than individuals, but there’s more to it than that. Population health relies on researchers in the healthcare field keeping track of disease occurrence in various groups of individuals. They could, for example, compare Covid-19 outbreaks among people of various populations living in various ZIP codes. Its goal is to employ screening to prevent or identify disease in big groups of people. This is distinct from more broad public health, which looks at the health of a whole group of people. Taking care of the public’s health necessitates a thorough examination of toxins in the air and water. The investigation of illness incidence in groups based on factors such as age, gender, or geography is required when it comes to population health.

When it comes to AI in healthcare, it’s safe to state that no amount of technology will ever be able to replace a human doctor’s informed judgment and experience treating members of the public – and no one wants it to. In the case of population health, which has become even more crucial since the epidemic, AI is needed now more than ever to supply professionals and public-health researchers with diagnosis and treatment statistics and other information. For analysis, population-health management software often integrates patient data from multiple healthcare IT systems. The information is utilized to improve the prediction and management of illnesses and disorders. The software is also utilized to make it easier to give care to different groups based on their needs. It caters to groups of individuals in some ways, but it ultimately serves to increase the quality of specialized patient care. After all, analyzing population data leads to more accurate big-picture representations of health patterns across different communities as well as better prediction of individual-health risks.

Throughout the epidemic, hospitals and affiliated clinics have turned to AI-enabled health technologies to boost resource efficiency, reinforce diagnoses, and manage patient volumes. This is very important in preventative care, particularly when it comes to orthopedic surgery. The number of orthopedic procedures performed worldwide is predicted to increase from 22.3 million in 2017 to 28.3 million in 2022. When you consider the scarcity of resources, surgeons, clinicians, and radiologists are put under a lot of stress.

Precision medicine can only work if data is processed and analyzed correctly. The AI models are already capable; all they require is data to work with. Emedgene, a genetic-interpretation company, coined the term “cognitive genomic intelligence” to describe a broad, ever-expanding platform that automatically generates insights from genomic data, reducing the time and cost of interpretation, which currently requires hours of manual review and yields limited results when relying solely on human intelligence.