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Artificial Intelligence & COVID-19: Applications, Impact, and Future Scope

The medical industry is searching for new technologies to monitor and control the spread of the COVID-19 (Coronavirus) pandemic in…

By folkduck , in Technology , at March 19, 2022

The medical industry is searching for new technologies to monitor and control the spread of the COVID-19 (Coronavirus) pandemic in this worldwide health crisis at this time. AI is a technology that can track the spread of this virus, identify high-risk patients, and assist in real-time control of this disease. It can also predict the likelihood of a patient’s death based on their medical history. To combat this virus, AI can help us by providing population screening, medical assistance, and advice on infection control. COVID-19 patients’ treatment plans, treatments, and reported outcomes could all be improved with the help of this medically proven technology.

Generally speaking, AI is effective and can identify and analyze patterns in large, complex data sets with greater precision and speed than has ever been possible before. As a further benefit, it can be used to conduct a thorough search of previous literary studies on the development of different drugs. Furthermore, robots infused with AI technology are used in the pharmaceutical manufacturing process, allowing for lightning-fast service. Artificial Intelligence (AI) can help the healthcare industry find suitable patients for clinical studies.

Fast-tracking systems in AI enable it to read radiological reports using deep learning and machine learning systems, reducing the workload of radiologists even further. The COVID-19 crisis is better understood and addressed thanks to AI and ML. The AI and Machine Learning bootcamp is a comprehensive training program for professionals working in AI and ML.

AI and machine learning employment will rise by 22% by 2030, almost three times the average growth rate for all occupations.

With the help of artificial intelligence (AI), diseases can be identified and monitored; one can predict outbreaks; mortality rates can be calculated; the disease can be diagnosed (COVID-19), and one can allocate resources more efficiently. In the fight against COVID-19, several AI applications are drawing attention and boosting hopes.

  1. AI in prediction & tracking

As data from social media, phone calls, and news sites are mined for virus forecasting and early warning system development, You can use AI to identify high-risk areas, predict disease spread, as well as estimate mortality and morbidity rates. Covid-19 was expected to be an outbreak by Bluedot, which used machine learning to identify a cluster of pneumonia cases. HealthMap gathers publicly available information on COVID-19 and makes it easily accessible so that you can effectively track the spread of the disease. Artificial intelligence (AI) has recently been emphasized in identifying and forecasting COVID-19 outbreaks through multitudinal and multimodal data.

  1. AI in contact tracing

In COVID-19, one can use smart devices like watches, mobile phones, cameras, and a wide range of wearable devices for diagnosis, contact tracing, and efficient monitoring. AI4COVID-19 telemedicine applications rely on audio recordings of 2 s cough samples.

  1. COVID-19 case monitoring via AI

Artificial intelligence (AI) monitors patients and forecasts treatment outcomes in medical contexts. AI can prioritize ventilators and respiratory assistance in the Intensive Care Unit based on vital statistics and clinical parameters. As well as daily updates, storage and trend analysis, and treatment planning, one can utilize AI to forecast recovery or mortality in COVID-19.

  1. AI in protein structure prediction

AI can anticipate the structure of proteins required for virus entrance and reproduction, paving the way for rapid medication development. The Google Deep Mind AlphaFold method used deep residual networks (DRN) named ResNets to predict protein structures of membrane protein, protein 3a, nsp2, nsp4, nsp6, and papain-like C-terminal domain of SARS-CoV-2. Using high-resolution cryoelectron microscopy density maps and amino acid sequencing, DeepTracer calculated the protein complex structure of SARS-CoV-2.

  1. AI in therapeutic development

By speeding up lead discovery, virtual screening, and validation processes, AI can significantly reduce the time required to bring a medicine from bench to bed. AI can help speed up the process by evaluating the properties of existing approved and validated pharmaceuticals based on molecular descriptors and attributes, something a human expert may not be able to do. 

  1. AI in vaccine development

Never before has there been such a race to find a disease vaccine. Using AI can significantly speed up the pace of discovery. Ong et al. projected possible COVID-19 vaccine candidates utilizing the Vaxign reverse vaccinology-machine learning technology.

  1. AI in countering falsehoods

This pandemic has become an infodemic due to the flood of knowledge. Using social media to gather and share timely and accurate information will assist mitigate the impact of COVID-19. As a result, machine learning approaches can uncover trends and sentiment analysis, helping to dispel myths and disinformation. One can also use AI to visualize recovery rates, healthcare accessibility, and availability and identify deficiencies. In this highly dynamic circumstance, AI can deliver the latest updates on developing evidence in diagnosis, treatment, symptom spectrum, and therapeutic outcomes, assisting physicians and the public in overcoming dread and panic.

AI and data science growth in old industries

Some industries, like mining, energy, manufacturing, and food production (chicken processing, meat processing), will adopt AI tools like computer vision and robots out of need. At the same time, other businesses may find themselves unexpectedly able to adopt AI. As society has become increasingly reliant on technology, many companies have digitized their internal processes and products and services; as customers explore non- and low-contact ways to communicate with organizations, companies that make the digital jump will be more likely to survive. The lack of digitization in many old-school organizations has made AI implementation problematic. These businesses and industries may find that digitizing allows them to use Analytics and AI.

Final words: Democratization of AI and ML

The expanding infrastructure and accessibility of AI and ML will empower enterprises of all sizes to disrupt sectors. Tools and AI democratization benefit smaller enterprises striving to innovate and disrupt their industries. Machine learning systems will require less effort and expertise as the methodologies and technical infrastructure needed to implement them become standardized.

AI’s essential nature is to collect data to maximize efficiency. As the pandemic’s economic shock compels sectors to transition to digital solutions, AI will have a lot of data and issues to tackle. While humans may never return to their former selves, AI is ready to welcome a new era.


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