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.

Sick on the Frontlines:A Cross Sectional Study on COVID-19 Infection, Symptom Severity Amongst Emergency Medicine Residents and Fellows in Urban Academic Hospital Settings (Preprint)

2021 ◽  
Author(s):  
Stacey Frisch ◽  
Sarah Jones ◽  
James Willis ◽  
Richard Sinert
Keyword(s):  
New York ◽  
Emergency Medicine ◽  
Cross Sectional Study ◽  
The Novel ◽  
Academic Hospital ◽  
Cross Sectional ◽  
Time Period ◽  
High Infection ◽  
Novel Coronavirus ◽  
Specific Symptoms

BACKGROUND COVID-19, an illness caused by the novel coronavirus SARS-CoV-2, affected many aspects of healthcare worldwide in 2020. From March to May of 2020, New York City (NYC) experienced a large surge of cases. OBJECTIVE The authors aimed to characterize the amount of illness experienced by residents and fellows in 2 NYC hospitals during this time period. METHODS This was a cross-sectional observational study. An IRB-exempt survey was distributed to emergency medicine housestaff in May 2020 and submissions were accepted through August 2020. RESULTS 64 residents and fellows responded to our survey (a 62% response rate). 42% of responders tested positive for SARS-CoV-2 antibodies. Most residents experienced symptoms that could be consistent with COVID-19 however few received PCR testing. Fevers and/or chills along with loss of smell and/or taste were the most specific symptoms for COVID-19, with p-values <0.05. All 13 housestaff who reported no symptoms during the study period tested negative for SARS-CoV-2 antibodies. CONCLUSIONS Our study demonstrated that the rate of COVID-19 illness among emergency department housestaff is much higher than previously reported. Further studies are needed to characterize illness among medical staff in emergency departments across the nation. The high infection rate among emergency medicine trainees stresses the importance of supplying adequate PPE for healthcare professionals.

scholarly journals The Upsurge and Impact of COVID 19 in India: Health Issues and Remedial Measures

2021 ◽  
pp. 28-34
Author(s):  
Kanchi Isswani
Keyword(s):  
Sudden Increase ◽  
The Novel ◽  
Health Issues ◽  
Public Places ◽  
Frontline Workers ◽  
Time Period ◽  
Essential Services ◽  
Novel Coronavirus ◽  
Major Decision ◽  
Better Than

The novel Coronavirus was something that nobody was prepared for. It was that part of the syllabus which was always neglected. The contagious disease which started in the Wuhan region of China had started to settle in various parts of the World. The outbreak of this disease has reached such a huge number that all the countries witnessed lockdown in some form or the other. Some people have witnessed destruction of mankind while some have even leisured this time to their fullest but as it has been always said “Prevention is better than cure”. Prevention of covid 19 in all the nations was one of the major steps which was taken in the year 2020. In India it all started in the year of 2019 December when the first ever case of covid 19 was reported in the state of Kerala followed by Rajasthan, Maharashtra and Delhi. Following such a situation and then sudden increase in the no of cases all over the country a major decision was taken that was of Complete lockdown excluding the emergency and essential services. Before taking the step of lockdown, as a gesture of respect to the frontline workers, government of India announced Tali Bajao movement. In the period of lockdown Certain norms were even made mandatory that were wearing a mask, maintenance of hand sanitation and following social distancing of 1.5 meters in public places. All the educational institutes and teachings were even suspended during the time period of lockdown as it could have become a hub for the virus to spread. With time, the restrictions which were laid down in lockdown were started to be reduced in the phase wise manner and finally India noticed its very first Unlock period. In all this scenario mankind has dealt with various situations and have emerged to be a better person. All these steps were crucial to control the spread of Novel Coronavirus and prevention from the already spread cases.

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.

Sick on the Frontlines: A Cross-Sectional Study on COVID-19 Infection, Symptom Severity Amongst Emergency Medicine Residents and Fellows in Urban Academic Hospital Settings (Preprint)

2021 ◽  
Author(s):  
Stacey Frisch ◽  
Sarah Jones ◽  
James Willis ◽  
Richard Sinert
Keyword(s):  
New York ◽  
Emergency Medicine ◽  
Cross Sectional Study ◽  
The Novel ◽  
Academic Hospital ◽  
Cross Sectional ◽  
Time Period ◽  
High Infection ◽  
Novel Coronavirus ◽  
Specific Symptoms

BACKGROUND COVID-19, an illness caused by the novel coronavirus SARS-CoV-2, affected many aspects of healthcare worldwide in 2020. From March to May of 2020, New York City (NYC) experienced a large surge of cases. OBJECTIVE The authors aimed to characterize the amount of illness experienced by residents and fellows in 2 NYC hospitals during this time period. METHODS This was a cross-sectional observational study. An IRB-exempt survey was distributed to emergency medicine housestaff in May 2020 and submissions were accepted through August 2020. RESULTS 64 residents and fellows responded to our survey (a 62% response rate). 42% of responders tested positive for SARS-CoV-2 antibodies. Most residents experienced symptoms that could be consistent with COVID-19 however few received PCR testing. Fevers and/or chills along with loss of smell and/or taste were the most specific symptoms for COVID-19, with p-values <0.05. All 13 housestaff who reported no symptoms during the study period tested negative for SARS-CoV-2 antibodies. CONCLUSIONS Our study demonstrated that the rate of COVID-19 illness among emergency department housestaff is much higher than previously reported. Further studies are needed to characterize illness among medical staff in emergency departments across the nation. The high infection rate among emergency medicine trainees stresses the importance of supplying adequate PPE for healthcare professionals.

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 Monitoring the COVID-19 epidemic with nationwide telecommunication data

2021 ◽  
Vol 118 (26) ◽  
pp. e2100664118
Author(s):  
Joel Persson ◽  
Jurriaan F. Parie ◽  
Stefan Feuerriegel
Keyword(s):  
Large Scale ◽  
Human Mobility ◽  
Human Movement ◽  
Spatiotemporal Analysis ◽  
Decision Makers ◽  
The Novel ◽  
School Closures ◽  
Time Period ◽  
Policy Measures ◽  
Novel Coronavirus

In response to the novel coronavirus disease (COVID-19), governments have introduced severe policy measures with substantial effects on human behavior. Here, we perform a large-scale, spatiotemporal analysis of human mobility during the COVID-19 epidemic. We derive human mobility from anonymized, aggregated telecommunication data in a nationwide setting (Switzerland; 10 February to 26 April 2020), consisting of ∼1.5 billion trips. In comparison to the same time period from 2019, human movement in Switzerland dropped by 49.1%. The strongest reduction is linked to bans on gatherings of more than five people, which are estimated to have decreased mobility by 24.9%, followed by venue closures (stores, restaurants, and bars) and school closures. As such, human mobility at a given day predicts reported cases 7 to 13 d ahead. A 1% reduction in human mobility predicts a 0.88 to 1.11% reduction in daily reported COVID-19 cases. When managing epidemics, monitoring human mobility via telecommunication data can support public decision makers in two ways. First, it helps in assessing policy impact; second, it provides a scalable tool for near real-time epidemic surveillance, thereby enabling evidence-based policies.

scholarly journals CORONA CASE PREDICTOR

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Sumer Sharma ◽  
Namita Goyal
Keyword(s):  
Data Model ◽  
Diagnostic Techniques ◽  
The Novel ◽  
Accurate Analysis ◽  
Global Migration ◽  
Time Period ◽  
The One ◽  
Novel Coronavirus ◽  
Second Wave ◽  
Official Data

What will be the further impact of the novel coronavirus (COVID-19) in India? To answer this question, we need an accurate analysis of the rate of death and recovery. At the same time, since the future does not usually repeat itself in the same way as in the past, so there is no certainty. The COVID-19 epidemic after spreading its roots to 206 countries around the world, has started again with more deadly waves than previous. Though vaccines are available now but still no one knows for how much time period certain vaccine can provide antibodies. So, the battle is still going on. Disease and death not only threaten people but also their economic impact. Even though if one got recovered from disease but post covid symptoms are the one which are haunting even more. Based on the official data model, diagnostic techniques are used to create a predictable but decisive prediction model for the spread of COVID-19 in India. The second wave of COVID-19 hit in the states of India during March and has since spread again to all other provinces with a great havoc and the situation is getting worse in countries with high global migration.

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