Background and aims Healthcare delivery requires the support of new technologies like Artificial Intelligence (AI), Internet of Things (IoT), Big Data and Machine Learning to fight and look ahead against the new diseases. We aim to review the role of AI as a decisive technology to analyze, prepare us for prevention and fight with COVID-19 (Coronavirus) and other pandemics. Methods The rapid review of the literature is done on the database of Pubmed, Scopus and Google Scholar using the keyword of COVID-19 or Coronavirus and Artificial Intelligence or AI. Collected the latest information regarding AI for COVID-19, then analyzed the same to identify its possible application for this disease. Results We have identified seven significant applications of AI for COVID-19 pandemic. This technology plays an important role to detect the cluster of cases and to predict where this virus will affect in future by collecting and analyzing all previous data. Conclusions Healthcare organizations are in an urgent need for decision-making technologies to handle this virus and help them in getting proper suggestions in real-time to avoid its spread. AI works in a proficient way to mimic like human intelligence. It may also play a vital role in understanding and suggesting the development of a vaccine for COVID-19. This result-driven technology is used for proper screening, analyzing, prediction and tracking of current patients and likely future patients. The significant applications are applied to tracks data of confirmed, recovered and death cases.

Artificial Intelligence (AI) applications for COVID-19 pandemic.

Background and objective During the recent global urgency, scientists, clinicians, and healthcare experts around the globe keep on searching for a new technology to support in tackling the Covid-19 pandemic The evidence of Machine Learning (ML) and Artificial Intelligence (AI) application on the previous epidemic encourage researchers by giving a new angle to fight against the novel Coronavirus outbreak This paper aims to comprehensively review the role of AI and ML as one significant method in the arena of screening, predicting, forecasting, contact tracing, and drug development for SARS-CoV-2 and its related epidemic Method A selective assessment of information on the research article was executed on the databases related to the application of ML and AI technology on Covid-19 Rapid and critical analysis of the three crucial parameters, ie, abstract, methodology, and the conclusion was done to relate to the model's possibilities for tackling the SARS-CoV-2 epidemic Result This paper addresses on recent studies that apply ML and AI technology towards augmenting the researchers on multiple angles It also addresses a few errors and challenges while using such algorithms in real-world problems The paper also discusses suggestions conveying researchers on model design, medical experts, and policymakers in the current situation while tackling the Covid-19 pandemic and ahead Conclusion The ongoing development in AI and ML has significantly improved treatment, medication, screening, prediction, forecasting, contact tracing, and drug/vaccine development process for the Covid-19 pandemic and reduce the human intervention in medical practice However, most of the models are not deployed enough to show their real-world operation, but they are still up to the mark to tackle the SARS-CoV-2 epidemic

Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review

Background and aim The current global challenge of COVID-19 pandemic has surpassed the provincial, radical, conceptual, spiritual, social, and pedagogical boundaries. Internet of Things (IoT) enabled healthcare system is useful for proper monitoring of COVID-19 patients, by employing an interconnected network. This technology helps to increase patient satisfaction and reduces readmission rate in the hospital. Methods Searched the databases of Google Scholar, PubMed, SCOPUS and ResearchGate using the keywords "Internet of things" or "IoT" and "COVID-19". Further inputs are also taken from blogs and relevant reports. Results IoT implementation impacts on reducing healthcare cost and improve treatment outcome of the infected patient. Therefore, this present study based research is attempted to explore, discuss, and highlight the overall applications of the well-proven IoT philosophy by offering a perspective roadmap to tackle the COVID-19 pandemic. Finally, twelve significant applications of IoT are identified and discussed. It has ultimately forced the researchers, academicians, and scientists to propose some productive solutions to overcome or confront this pandemic. Conclusions IoT is helpful for an infected patient of COVID-19 to identify symptoms and provides better treatment rapidly. It is useful for patient, physician, surgeon and hospital management system.

Internet of things (IoT) applications to fight against COVID-19 pandemic.

The new Coronavirus (COVID-19) is an emerging disease responsible for infecting millions of people since the first notification until nowadays. Developing efficient short-term forecasting models allow forecasting the number of future cases. In this context, it is possible to develop strategic planning in the public health system to avoid deaths. In this paper, autoregressive integrated moving average (ARIMA), cubist regression (CUBIST), random forest (RF), ridge regression (RIDGE), support vector regression (SVR), and stacking-ensemble learning are evaluated in the task of time series forecasting with one, three, and six-days ahead the COVID-19 cumulative confirmed cases in ten Brazilian states with a high daily incidence. In the stacking-ensemble learning approach, the CUBIST regression, RF, RIDGE, and SVR models are adopted as base-learners and Gaussian process (GP) as meta-learner. The models' effectiveness is evaluated based on the improvement index, mean absolute error, and symmetric mean absolute percentage error criteria. In most of the cases, the SVR and stacking-ensemble learning reach a better performance regarding adopted criteria than compared models. In general, the developed models can generate accurate forecasting, achieving errors in a range of 0.87%-3.51%, 1.02%-5.63%, and 0.95%-6.90% in one, three, and six-days-ahead, respectively. The ranking of models, from the best to the worst regarding accuracy, in all scenarios is SVR, stacking-ensemble learning, ARIMA, CUBIST, RIDGE, and RF models. The use of evaluated models is recommended to forecasting and monitor the ongoing growth of COVID-19 cases, once these models can assist the managers in the decision-making support systems.

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Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil.

Industry 5.0: A survey on enabling technologies and potential applications

Background/objectives The Internet of Things (IoT) can create disruptive innovation in healthcare Thus, during COVID-19 Pandemic, there is a need to study different applications of IoT enabled healthcare For this, a brief study is required for research directions Methods Research papers on IoT in healthcare and COVID-19 Pandemic are studied to identify this technology’s capabilities This literature-based study may guide professionals in envisaging solutions to related problems and fighting against the COVID-19 type pandemic Results Briefly studied the significant achievements of IoT with the help of a process chart Then identifies seven major technologies of IoT that seem helpful for healthcare during COVID-19 Pandemic Finally, the study identifies sixteen basic IoT applications for the medical field during the COVID-19 Pandemic with a brief description of them Conclusions In the current scenario, advanced information technologies have opened a new door to innovation in our daily lives Out of these information technologies, the Internet of Things is an emerging technology that provides enhancement and better solutions in the medical field, like proper medical record-keeping, sampling, integration of devices, and causes of diseases IoT’s sensor-based technology provides an excellent capability to reduce the risk of surgery during complicated cases and helpful for COVID-19 type pandemic In the medical field, IoT’s focus is to help perform the treatment of different COVID-19 cases precisely It makes the surgeon job easier by minimising risks and increasing the overall performance By using this technology, doctors can easily detect changes in critical parameters of the COVID-19 patient This information-based service opens up new healthcare opportunities as it moves towards the best way of an information system to adapt world-class results as it enables improvement of treatment systems in the hospital Medical students can now be better trained for disease detection and well guided for the future course of action IoT’s proper usage can help correctly resolve different medical challenges like speed, price, and complexity It can easily be customised to monitor calorific intake and treatment like asthma, diabetes, and arthritis of the COVID-19 patient This digitally controlled health management system can improve the overall performance of healthcare during COVID-19 pandemic days

Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic

Telemedicine (TM) is used to treat patients in a remote location by using telecommunication technology. It exchanges the medical information and data from one location to another through advanced t...

Ibrahim Haleem Khan

Papers

Artificial Intelligence (AI) applications for COVID-19 pandemic.

Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic

Telemedicine Technologies for Confronting COVID-19 Pandemic: A Review

Current status and applications of Artificial Intelligence (AI) in medical field: An overview

Artificial Intelligence (AI) applications in orthopaedics: An innovative technology to embrace.