scholarly journals COVID-19 Pandemic: How to Use Artificial Intelligence to Choose Non-Vulnerable Workers for Positions with the Highest Possible Levels of Exposure to the Novel Coronavirus

2020 ◽  
Vol 10 (3) ◽  
Keyword(s):  
Artificial Intelligence ◽  
The Novel ◽  
Novel Coronavirus ◽  
Vulnerable Workers

Use of Artificial Intelligence (AI) in Fighting With the Novel Coronavirus (COVID-19)

2021 ◽  
pp. 21-30
Author(s):  
Anuja Rajendra Jadhav ◽  
Roshani Raut ◽  
Ram Joshi ◽  
Pranav D. Pathak ◽  
Anuja R. Zade
Keyword(s):  
Artificial Intelligence ◽  
Drug Discovery ◽  
Active Learning ◽  
The Novel ◽  
Response Recovery ◽  
Control And Prevention ◽  
Virus Attack ◽  
Detection Response ◽  
Novel Coronavirus

2020 started with the outbreak of the novel coronavirus (COVID-19) virus. In this panic situation, the combination of artificial intelligence (AI) can help us in fight against the deadliest virus attack worldwide. This tool can be used to control and prevention of the outbreak disease. The AI tool can be helpful in prediction, detection, response, recovery, drug discovery of the disease. The AI-driven tools can be used in identifying the nature of outbreak as well as in forecasting the spread and coverage worldwide. In this case, so many AI-based tools can be applied and trained using active learning-based models for the detection, prevention, treatment, and recovery of the patients. Also, they can help us for identifying infected persons from the non-infected to stop the spread of the virus. This chapter mainly focuses on the AI-assisted methodology and models that can help in fighting COVID-19.

scholarly journals AI Chatbot Design during an Epidemic like the Novel Coronavirus

Healthcare ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 154 ◽  
Author(s):  
Gopi Battineni ◽  
Nalini Chintalapudi ◽  
Francesco Amenta
Keyword(s):  
Artificial Intelligence ◽  
Preventive Measures ◽  
Diagnostic Evaluation ◽  
The Novel ◽  
Healthcare Staff ◽  
Medical Specialist ◽  
Remote Areas ◽  
Global Pandemic ◽  
Novel Coronavirus

Since the discovery of the Coronavirus (nCOV-19), it has become a global pandemic. At the same time, it has been a great challenge to hospitals or healthcare staff to manage the flow of the high number of cases. Especially in remote areas, it is becoming more difficult to consult a medical specialist when the immediate hit of the epidemic has occurred. Thus, it becomes obvious that if effectively designed and deployed chatbot can help patients living in remote areas by promoting preventive measures, virus updates, and reducing psychological damage caused by isolation and fear. This study presents the design of a sophisticated artificial intelligence (AI) chatbot for the purpose of diagnostic evaluation and recommending immediate measures when patients are exposed to nCOV-19. In addition, presenting a virtual assistant can also measure the infection severity and connects with registered doctors when symptoms become serious.

scholarly journals Bayesian Reasoning and Artificial Intelligence against COVID-19

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Michael Gr. Voskoglou ◽  
Abdel-Badeeh M. Salem
Keyword(s):  
Artificial Intelligence ◽  
World Economy ◽  
Potential Role ◽  
Reproduction Number ◽  
Case Based Reasoning ◽  
Bayesian Reasoning ◽  
The Novel ◽  
The World ◽  
Novel Coronavirus

The article focuses on the potential role of Probability Theory and Artificial Intelligence in the battle against the pandemic of COVID-19, which, starting from China on December 2019, has created a chaos in the world economy and the lives of people, causing hundreds of thousands of deaths until now. After discussing the importance of the reproduction number Ro of the viruses, the Bayesian Probabilities are used for measuring the creditability of the diagnostic tests for the novel coronavirus. Artificial Intelligence designs are also described which are used as tools against COVID-19 and a Case-Based Reasoning expert system is proposed for the COVID-19 diagnosis.

scholarly journals MantisCOVID: Rapid X-Ray Chest Radiograph and Mortality Rate Evaluation With Artificial Intelligence For COVID-19

2020 ◽  
Author(s):  
Yağmur Yaşar ◽  
Berat Tuna Karli ◽  
Cem Çöteli ◽  
Mert Burkay Çöteli
Keyword(s):  
Artificial Intelligence ◽  
Mortality Rate ◽  
Chest Radiograph ◽  
Well Being ◽  
Health Economy ◽  
Diagnostic Tools ◽  
Healthy Population ◽  
The Novel ◽  
X Ray ◽  
Novel Coronavirus

AbstractThe novel coronavirus pandemic has negative impacts over the health, economy and well-being of the global population. This negative effect is growing with the high spreading rate of the virus. The most critical step to prevent the spreading of the virus is pre-screening and early diagnosis of the individuals. This results in quaranteeing the patients not to effect the healthy population. COVID-19 is the name of the disease caused by the novel coronavirus. It has a high infection rate and it is urgent to diagnose many patients as we can to prevent the spread of the virus at the early stage. Rapid diagnostic tools development is urgent to save lives. MantisCOVID is a cloud-based pre-diagnosis tool to be accessed from the internet. This tool delivers a rapid screening test by analyzing the X-ray Chest Radiograph scans via Artificial Intelligence (AI) and it also evaluates the mortality rate of patients with the synthesis of the patient’s history with the machine learning methods. This study reveals the methods used over the platform and evaluation of the algorithms via open datasets.

scholarly journals What Will Affect the Diffusion of AI Agents?

2021 ◽  
Vol 3 ◽  
pp. 83-89
Author(s):  
James Dearing
Keyword(s):  
Artificial Intelligence ◽  
Uses And Gratifications ◽  
Societal Change ◽  
The Novel ◽  
Expectancy Violations ◽  
User Perspective ◽  
Time Period ◽  
Novel Coronavirus ◽  
Machine Communication

For billions of people, the threat of the Novel Coronavirus SARS-CoV-2 and its variants has precipitated the adoption of new behaviors. Pandemics are radical events that disrupt the gradual course of societal change, offering the possibility that some rapidly adopted innovations will persist in use past the time period of the event and, thus, diffuse more rapidly than in the absence of such an event. Human-machine communication includes a range of technologies with which many of us have quickly become more familiar due to stay-athome orders, distancing, workplace closures, remote instruction, home-bound entertainment, fear of contracting COVID-19, and boredom. In this commentary I focus on Artificial Intelligence (AI) agents, and specifically chatbots, in considering the factors that may affect chatbot diffusion. I consider anthropomorphism and expectancy violations, the characteristics of chatbots, business imperatives, millennials and younger users, and from the user perspective, uses and gratifications.

scholarly journals COVID-19 in Brazil—Preliminary Analysis of Response Supported by Artificial Intelligence in Municipalities

2021 ◽  
Vol 3 ◽  
Author(s):  
Hugo M. P. Morales ◽  
Murilo Guedes ◽  
Jennifer S. Silva ◽  
Adriano Massuda
Keyword(s):  
Artificial Intelligence ◽  
Health System ◽  
Low Income ◽  
Health Care Systems ◽  
Low Income Countries ◽  
The Novel ◽  
Continuous Increase ◽  
Care Systems ◽  
Source Of Care ◽  
Novel Coronavirus

The novel coronavirus disease (COVID-19) forced rapid adaptations in the way healthcare is delivered and coordinated by health systems. Brazil has a universal public health system (Sistema Unico de Saúde—SUS), being the main source of care for 75% of the population. Therefore, a saturation of the system was foreseen with the continuous increase of cases. The use of Artificial Intelligence (AI) to empower telehealth could help to tackle this by increasing a coordinated patient access to the health system. In the present study we describe a descriptive case report analyzing the use of Laura Digital Emergency Room—an AI-powered telehealth platform—in three different cities. It was computed around 130,000 interactions made by the chatbot and 24,162 patients completed the digital triage. Almost half (44.8%) of the patients were classified as having mild symptoms, 33.6% were classified as moderate and only 14.2% were classified as severe. The implementation of an AI-powered telehealth to increase accessibility while maintaining safety and leveraging value amid the unprecedent impact of the COVID-19 pandemic was feasible in Brazil and may reduce healthcare overload. New efforts to yield sustainability of affordable and scalable solutions are needed to truly leverage value in health care systems, particularly in the context of middle-low-income countries.

scholarly journals COV-DrugX Pipeline for Covid-19 Drug Repurposing

2021 ◽  
Author(s):  
Robin Sinha ◽  
Preeti P
Keyword(s):  
Artificial Intelligence ◽  
Drug Discovery ◽  
De Novo ◽  
Drug Repurposing ◽  
Therapeutic Agents ◽  
The Novel ◽  
Novel Coronavirus ◽  
The Cost

The outbreak of the novel coronavirus disease COVID-19, caused by the SARS-CoV-2 virus has killed over 5 million people to date. Despite the introduction of population-wide vaccination drives, countries such as Austria and Germany are witnessing the re-emergence of infections and deaths. Scientists, administrators and clinicians are scrambling to find solutions that include vaccines, and active therapeutic agents. So, there is an urgent requirement for new and effective medications that can treat the disease caused by SARS-CoV-2. Artificial intelligence (AI) enabled drug repurposing, has the potential to shorten the time and reduce the cost compared to de novo drug discovery.

Artificial Intelligence in Medicine: Lessons from COVID-19 (Preprint)

2020 ◽  
Author(s):  
Joshua Hatherley
Keyword(s):  
Artificial Intelligence ◽  
Global Health ◽  
Cost Savings ◽  
Economic Structure ◽  
The Novel ◽  
High Stakes ◽  
Health Crisis ◽  
Patient Confidentiality ◽  
Government Aid ◽  
Novel Coronavirus

UNSTRUCTURED The dramatic effects of the novel coronavirus have been felt deeply worldwide. As of the time of writing, almost 600,000 lives have been lost, unemployment claims have reached record heights, and entire sectors of various economies have been largely shut down. Yet from tragedies of such grand scale, important lessons can be learned: about the economic structure of healthcare, about future systems of employment and government aid, and about the use of emerging technologies in medicine and healthcare. In this article, I focus upon the use of artificial intelligence in medicine, and identify two lessons that can be learned from the COVID-19 global health crisis. I argue that high-stakes scenarios like those emerging from COVID-19 pose an especially challenging tension between patient confidentiality and the efficacy of AI in medicine, and that confident predictions of cost-savings and greater efficiency ought to be eyed with suspicion.

Comparative docking of SARS-CoV-2 receptors antagonists from repurposing drugs

2020 ◽  
Author(s):  
Micael Davi Lima de Oliveira ◽  
Kelson Mota Teixeira de Oliveira
Keyword(s):  
World Health Organisation ◽  
World Health ◽  
Lung Cells ◽  
The Novel ◽  
High Modulation ◽  
Main Protease ◽  
The World ◽  
Novel Coronavirus ◽  
Viral Receptors ◽  
Theoretical Results

According to the World Health Organisation, until 16 June, 2020, the number of confirmed and notified cases of COVID-19 has already exceeded 7.9 million with approximately 434 thousand deaths worldwide. This research aimed to find repurposing antagonists, that may inhibit the activity of the main protease (Mpro) of the SARS-CoV-2 virus, as well as partially modulate the ACE2 receptors largely found in lung cells, and reduce viral replication by inhibiting Nsp12 RNA polymerase. Docking molecular simulations were performed among a total of 60 structures, most of all, published in the literature against the novel coronavirus. The theoretical results indicated that, in comparative terms, paritaprevir, ivermectin, ledipasvir, and simeprevir, are among the most theoretical promising drugs in remission of symptoms from the disease. Furthermore, also corroborate indinavir to the high modulation in viral receptors. The second group of promising drugs includes remdesivir and azithromycin. The repurposing drugs HCQ and chloroquine were not effective in comparative terms to other drugs, as monotherapies, against SARS-CoV-2 infection.

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