scholarly journals Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining

2021 ◽  
Vol 18 (16) ◽  
pp. 8578
Author(s):  
Ignacio Rodríguez-Rodríguez ◽  
José-Víctor Rodríguez ◽  
Niloofar Shirvanizadeh ◽  
Andrés Ortiz ◽  
Domingo-Javier Pardo-Quiles
Keyword(s):  
Artificial Intelligence ◽  
Text Mining ◽  
The United States ◽  
Social Consequences ◽  
Current Status ◽  
Automatic Process ◽  
Scientometric Analysis ◽  
Wide Range ◽  
Health Related ◽  
Current Lines

The COVID-19 pandemic has wreaked havoc in every country in the world, with serious health-related, economic, and social consequences. Since its outbreak in March 2020, many researchers from different fields have joined forces to provide a wide range of solutions, and the support for this work from artificial intelligence (AI) and other emerging concepts linked to intelligent data analysis has been decisive. The enormous amount of research and the high number of publications during this period makes it difficult to obtain an overall view of the different applications of AI to the management of COVID-19 and an understanding of how research in this field has been evolving. Therefore, in this paper, we carry out a scientometric analysis of this area supported by text mining, including a review of 18,955 publications related to AI and COVID-19 from the Scopus database from March 2020 to June 2021 inclusive. For this purpose, we used VOSviewer software, which was developed by researchers at Leiden University in the Netherlands. This allowed us to examine the exponential growth in research on this issue and its distribution by country, and to highlight the clear hegemony of the United States (USA) and China in this respect. We used an automatic process to extract topics of research interest and observed that the most important current lines of research focused on patient-based solutions. We also identified the most relevant journals in terms of the COVID-19 pandemic, demonstrated the growing value of open-access publication, and highlighted the most influential authors by means of an analysis of citations and co-citations. This study provides an overview of the current status of research on the application of AI to the pandemic.

scholarly journals Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zaid Nabulsi ◽  
Andrew Sellergren ◽  
Shahar Jamshy ◽  
Charles Lau ◽  
Edward Santos ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Imaging Modality ◽  
General Setting ◽  
The United States ◽  
Turnaround Time ◽  
City Hospital ◽  
Large Dataset ◽  
Clinical Imaging ◽  
Abnormal Chest ◽  
Wide Range

AbstractChest radiography (CXR) is the most widely-used thoracic clinical imaging modality and is crucial for guiding the management of cardiothoracic conditions. The detection of specific CXR findings has been the main focus of several artificial intelligence (AI) systems. However, the wide range of possible CXR abnormalities makes it impractical to detect every possible condition by building multiple separate systems, each of which detects one or more pre-specified conditions. In this work, we developed and evaluated an AI system to classify CXRs as normal or abnormal. For training and tuning the system, we used a de-identified dataset of 248,445 patients from a multi-city hospital network in India. To assess generalizability, we evaluated our system using 6 international datasets from India, China, and the United States. Of these datasets, 4 focused on diseases that the AI was not trained to detect: 2 datasets with tuberculosis and 2 datasets with coronavirus disease 2019. Our results suggest that the AI system trained using a large dataset containing a diverse array of CXR abnormalities generalizes to new patient populations and unseen diseases. In a simulated workflow where the AI system prioritized abnormal cases, the turnaround time for abnormal cases reduced by 7–28%. These results represent an important step towards evaluating whether AI can be safely used to flag cases in a general setting where previously unseen abnormalities exist. Lastly, to facilitate the continued development of AI models for CXR, we release our collected labels for the publicly available dataset.

scholarly journals Medical Speech-Language Pathology in Bulgaria – a Comparative Study of the Current Status and Development

2021 ◽  
Vol 4 (1) ◽  
pp. 8-16
Keyword(s):  
Comparative Analysis ◽  
The United States ◽  
Scope Of Practice ◽  
Current Status ◽  
Clear Understanding ◽  
Speech Language Pathology ◽  
Medical Environment ◽  
Wide Range ◽  
The Usa ◽  
Language Pathology

Introduction: The complexity of ever-changing health standards, new health policies, changes in the healthcare environment, necessitates an advanced level of professional expertise in Medical Speech-Language Pathology (MSLP). Objective: This study presents the current status, opportunities, and perspectives for the development of MSLP in Bulgaria. Method Theoretical overview and comparative analysis of the data and literature on MSLP as it exists in the USA and is developing in Bulgaria, where it is most often referred to as Clinical Logopedics. In this article, we present: (i) a comparative analysis of the development of this dynamic, expanding, and continuously developing health profession in the USA (the country with the most innovative and highly evolved practice of MSLP) and Bulgaria; (ii) brief historical notes related to the development of Speech-Language Pathology in the United States and Bulgaria; (iii) the scope of practice of MSLP in the USA and Bulgaria, which is a key problem for the prospects for the development of this specialty in Bulgaria, and (iv) the problems associated with establishing a master’s degree program in MSLP. Conclusion: MSLP has perspective for development in Bulgaria only if it is studied as a health specialty within medical or health faculties, but necessarily housed within a medical university. A clear understanding of the scope of practice is fundamental for the development of MSLP, but it should not overlap the purview of other professions. The MSLP master’s program should be innovative, manageable, and comprehensive, providing for a wide range of specialized clinical experiences that prepare students to practice effectively in a medical environment.

Measuring scientific fundamentals of public policies related to health through text mining (Preprint)

2018 ◽  
Author(s):  
Caroline Pauletto Spanhol-Finocchio ◽  
Mariana De Freitas Dewes ◽  
Giana De Vargas Mores ◽  
Homero Dewes
Keyword(s):  
Public Policy ◽  
Text Mining ◽  
Time Window ◽  
Public Policies ◽  
The United States ◽  
Scientific Basis ◽  
Early Care ◽  
Physical Sciences ◽  
The Public ◽  
Health Related

BACKGROUND Obesity has become a health problem worldwide, determined by multiple and complex factors, and face to this challenge, governments have played central role in combating its rise. Considering this fact, public policies are introduced or enacted for the benefit of whole populations, taking into account the prospective of multiverse social stakeholders based on solid scientific fundamentals. In an eventual evaluation of a proposed or enforced public policy it can be relevant to explicit the scientific roots of its directives. OBJECTIVE The aim of this study was to examine obesity-related policies in all US states and District of Columbia, in order to understand their scientific basis. METHODS We analyzed the public policies, as implemented in the United States, in the time window when this health-related trend was a major governmental concern. In total, 1,592 policies related to obesity were selected and analyzed through text mining technique. RESULTS The multidisciplinary area was predominant in the documents analyzed (33.5%), followed by Health Sciences (28.5%), Social Sciences (20.7%), Life Sciences (15.1%) and Physical Sciences (2.2%). Besides, throughout the country most policies were community oriented and many of them were related to school and family environments, early care and education, hospitals and workplaces. CONCLUSIONS The content of public policies analyzed have elements of science with predominance of multidisciplinary area. This results provide evidence of how science and public policy are interrelated. In the same time, it can drive government decisions related to investments on science.

Collier County, Florida: Consideration of Gasification as a Long-Term Waste Management Solution

2003 ◽  
Author(s):  
Stephen C. Schwarz ◽  
Daniel E. Dietch
Keyword(s):  
Waste Management ◽  
Solid Waste ◽  
Evaluation Process ◽  
The United States ◽  
Management Program ◽  
Waste To Energy ◽  
Current Status ◽  
Collier County ◽  
Wide Range

Collier County, Florida (“County”) is in the midst of developing an integrated waste management program. Unlike many counties, Collier County owns a landfill with sufficient long-term landfill capacity to last another 15 years. However, due to the Board of County Commissioner’s (“Board”) desire to have a 50-year solution for solid waste, the County has set upon a course to divert waste from the landfill to the maximum extent possible. In doing so, the County solicited long-term waste management solutions from private companies capable of processing the majority of the municipal solid waste generated in the County. Over the past two years, the County has considered several of these alternatives ranging from MSW composting to mass-burn waste-to-energy; however, based on an evaluation of a wide range of impacts, gasification was selected as the preferred alternative. With this focus, the County issued a Request for Proposal (“RFP”) in November 2001 for a design, build, own, operate, and finance gasification project. The County received three proposals in April 2002 in response to the RFP. To date, the County has completed the proposal evaluation process and has ranked the top two responsive firms: Interstate Waste Technologies (“IWT”) and Brightstar Environmental (Florida), LLC (“Brightstar”) based on experience, technical approach, business arrangement, and cost. If implemented, this project will be the only commercial gasification project operating in the United States. This paper will provide insight into various stages of the project, from development through to the current status of the project, as well as the strategic policy, financial, and technical considerations that make this opportunity a good fit for the County. An emphasis will also be placed on comparing and contrasting the benefits and drawbacks of each technology, such as processing methodology, cost, redundancy, and scalability.

scholarly journals Attitudes to Foreign Language Learning in New Zealand Schools

2021 ◽  
Author(s):  
◽  
Sandra Shearn
Keyword(s):  
New Zealand ◽  
Secondary School ◽  
Foreign Language ◽  
Language Learning ◽  
Foreign Language Learning ◽  
The United States ◽  
Retention Rates ◽  
Current Status ◽  
School Students ◽  
Wide Range

<p>This thesis examines attitudes towards the learning of languages other than English and Maori among New Zealand school students in years 8 and 9, parents of year 9 students, and a wide range of teachers. The research examined the extent to which participants subscribed to certain commonly held views about second language learning, for example: that it is too hard for most students, that it serves no purpose for future employment, that languages are 'girls' subjects', and so on. The investigation adopted a theoretical framework derived chiefly from the social psychological literature concerning language learning attitudes and motivation. Students were surveyed by means of questionnaires over two successive years in the same part of the country, so that it was possible to discover if the intentions of the year 8 students to study a foreign language when they started secondary school were carried out. Parents and teachers were interviewed to discover their experience of foreign language learning and their thoughts about its place in New Zealand schools and in their children's education. The findings are set against detailed information about each of the seven schools involved, the place of languages in the official curriculum framework and the Ministry of Education's efforts to promote language learning. For comparison, information is also presented on the recent history and current status of foreign language learning in the United Kingdom, the United States of America and Australia. It was found that attitudes towards foreign language learning, of both adults and children, were mostly positive. Although many teachers were pessimistic about the views of their colleagues and students' parents, the majority of all the adults believed that language learning was desirable and possible for all or most students for a range of reasons. The majority also supported an earlier start to language learning, most favouring year 7. The findings suggest that the main reason that the proportion of students starting a foreign language in year 9 remains around 50%, and that retention rates in subsequent years continue to drop, is that languages are optional for most secondary students. This research found that choosing to study a language often meant sacrificing other subjects which students would like to have tried, and thus depended on strong intrinsic motivation, Although no participants claimed that language learning was more suitable for girls, it was found that the majority of students who opted for, and continued, language learning were girls, that boys tended to prefer practical subjects, and that, in the case of one secondary school, the minority of boys who were permitted to start a foreign language were discouraged from continuing by the general organisation and ethos of the school. Ultimately, the research indicated that attitudes towards foreign language learning in schools involved a complex web of factors. External factors often outweighed even the most positive attitudes among students, parents and teachers when option subjects were chosen. The low level of language learning in New Zealand, contrasted with the importance it has in comparable countries, was shown to result not so much from negative attitudes but rather from barriers within the education system as a whole and individual school cultures.</p>

scholarly journals Big Data, artificial intelligence and the geography of entrepreneurship in the United States

2018 ◽  
Author(s):  
Martin Obschonka ◽  
Neil Lee ◽  
Andrés Rodríguez-Pose ◽  
johannes Christopher Eichstaedt ◽  
Tobias Ebert
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Big Data ◽  
Big Five ◽  
The United States ◽  
Economic Outcomes ◽  
Entrepreneurial Activity ◽  
Personality Profile ◽  
Artificial Intelligence Methods ◽  
Wide Range

There is increasing interest in the potential of artificial intelligence and Big Data (e.g., generated via social media) to help understand economic outcomes and processes. But can artificial intelligence models, solely based on publicly available Big Data (e.g., language patterns left on social media), reliably identify geographical differences in entrepreneurial personality/culture that are associated with entrepreneurial activity? Using a machine learning model processing 1.5 billion tweets by 5.25 million users, we estimate the Big Five personality traits and an entrepreneurial personality profile for 1,772 U.S. counties. We find that these Twitter-based personality estimates show substantial relationships to county-level entrepreneurship activity, accounting for 20% (entrepreneurial personality profile) and 32% (all Big Five trait as separate predictors in one model) of the variance in local entrepreneurship and are robust to the introduction in the model of conventional economic factors that affect entrepreneurship. We conclude that artificial intelligence methods, analysing publically available social media data, are indeed able to detect entrepreneurial patterns, by measuring territorial differences in entrepreneurial personality/culture that are valid markers of actual entrepreneurial behaviour. More importantly, such social media datasets and artificial intelligence methods are able to deliver similar (or even better) results than studies based on millions of personality tests (self-report studies). Our findings have a wide range of implications for research and practice concerned with entrepreneurial regions and eco-systems, and regional economic outcomes interacting with local culture.

scholarly journals Evolving Structure and Diversity of Human Narratives in the Journal of Stories in Science

2020 ◽  
Author(s):  
Reilly Q. Mach ◽  
Jessica W. Tsai ◽  
Fanuel J. Muindi
Keyword(s):  
The United States ◽  
Target Range ◽  
Racial Groups ◽  
Flesch Reading Ease ◽  
The People ◽  
Wide Range ◽  
Health Related ◽  
Ease Score ◽  
Detailed Assessment ◽  
K 12

AbstractFundamentally, science is about people. The stories of the people behind the science are just as important as the results themselves, even though the results are often what get more attention. Despite the growth of databases storing such stories across diverse mediums, a detailed assessment of those databases is missing. To continue innovating science storytelling, we provide the first assessment of the structure and diversity of the narratives published in the Journal of Stories in Science. In this assessment, a total of 170 published stories authored by 158 authors between 2016 and 2020 are analyzed. Majority (67%) of the authors are women from North America and in the life sciences. The narratives most commonly feature authors from academia (e.g., 23% graduate students, 13% post-doctoral fellows and 21% professors). However, there is also a growing number of authors with PhDs that are working outside of academia (15%). Nearly a quarter (23%) of the database authors come from racial groups (African American, Latino, and Hispanic) that have been shown to be underrepresented in health-related sciences in the United States. Using the industry standard Flesch Reading Ease Score, we found that 74% of the stories included in the analysis fall in the target range of 50-70, which represents readability by students in grades 8-12. The analysis here provides the first deep look into one of the databases publishing diverse stories in science using a wide range of mediums. In summary, there is a need for more emphasis on both expanding and studying such databases given the continuous demand for these stories and their inclusion into K-12 curriculums.

scholarly journals Scientometric and Methodological Analysis of the Recent Literature on the Health-Related Effects of Tomato and Tomato Products

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1905
Author(s):  
Francesca Tilesi ◽  
Andrea Lombardi ◽  
Andrea Mazzucato
Keyword(s):  
Recent Literature ◽  
Biological Effects ◽  
The United States ◽  
Scientometric Analysis ◽  
Tissue Analysis ◽  
Healthy Individuals ◽  
Cytotoxic Effects ◽  
Health Related

The health benefits of tomato, a vegetable consumed daily in human diets, have received great attention in the scientific community, and a great deal of experiments have tested their utility against several diseases. Herein, we present a scientometric analysis of recent works aimed to estimate the biological effects of tomato, focusing on bibliographic metadata, type of testers, target systems, and methods of analysis. A remarkably variable array of strategies was reported, including testers obtained by standard and special tomatoes, and the use of in vitro and in vivo targets, both healthy and diseased. In vitro, 21 normal and 36 cancer human cell lines derived from 13 different organs were used. The highest cytotoxic effects were reported on cancer blood cells. In vivo, more experiments were carried out with murine than with human systems, addressing healthy individuals, as well as stressed and diseased patients. Multivariate analysis showed that publications in journals indexed in the agriculture category were associated with the use of fresh tomatoes; conversely, medicine and pharmacology journals were associated with the use of purified and formulate testers. Studies conducted in the United States of America preferentially adopted in vivo systems and formulates, combined with blood and tissue analysis. Researchers in Italy, China, India, and Great Britain mostly carried out in vitro research using fresh tomatoes. Gene expression and proteomic analyses were associated with China and India. The emerging scenario evidences the somewhat dichotomic approaches of plant geneticists and agronomists and that of cell biologists and medicine researchers. A higher integration between these two scientific communities would be desirable to foster the assessment of the benefits of tomatoes to human health.

scholarly journals A scientometric analysis of COVID-19 vaccine publications

2021 ◽  
Vol 9 (3) ◽  
pp. 138-147
Author(s):  
Mehmet Oguzhan Ay ◽  
Ali Kemal Erenler ◽  
Ozlem Oymak Ay ◽  
Halil Kaya ◽  
Melih Yuksel ◽  
...  
Keyword(s):  
Core Collection ◽  
Web Of Science ◽  
The United States ◽  
Current Status ◽  
Future Perspective ◽  
Experimental Medicine ◽  
Scientometric Analysis ◽  
Medicine Research ◽  
General Internal ◽  
Number Of Publications

Coronavirus disease 2019 (COVID-19) caused by the novel coronavirus SARS-CoV-2 that was declared as a pandemic has been the main subject of research all over the world. Especially studies on COVID-19 vaccines has become a hope for everyone. In this study, we aimed to analyse entire literature through Web of Science© Core Collection Database and reveal the current status of COVID-19 vaccine literature. We entered the keywords “COVID-19” and “vaccine” to Web of Science© Core Collection Database on January 20, 2021. Web of Science categories, document types, organizations, funding agencies, authors, journals, countries, languages, study fields, were investigated. A total of 2,765 publications with 24,202 citations times were involved into the study. Majority of the publications were original articles. Immunology, General Internal Medicine and Experimental Medicine Research were the top categories. Top productive Universities were Harvard University, University of California System and University of London. Dhama K. had the highest number of publications followed by Mahase E. and Baric RS. Journal of Biomolecular Structure Dynamics had published the highest number of publications. Majority of the publications were written in English. The United States of America was the most productive country followed by China and India. Research in vaccines is a growing field and is an essential component in the fight against COVID-19. Detailed analyses on vaccine publications may help researchers determine the future perspective.

scholarly journals Exploring perceptions of healthcare technologies enabled by artificial intelligence: an online, scenario-based survey

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alison L. Antes ◽  
Sara Burrous ◽  
Bryan A. Sisk ◽  
Matthew J. Schuelke ◽  
Jason D. Keune ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Healthcare System ◽  
Online Survey ◽  
The United States ◽  
Full Time ◽  
Psychosocial Variables ◽  
Perceived Benefit ◽  
Health Related ◽  
Healthcare Technologies ◽  
Trust In Technology

Abstract Background Healthcare is expected to increasingly integrate technologies enabled by artificial intelligence (AI) into patient care. Understanding perceptions of these tools is essential to successful development and adoption. This exploratory study gauged participants’ level of openness, concern, and perceived benefit associated with AI-driven healthcare technologies. We also explored socio-demographic, health-related, and psychosocial correlates of these perceptions. Methods We developed a measure depicting six AI-driven technologies that either diagnose, predict, or suggest treatment. We administered the measure via an online survey to adults (N = 936) in the United States using MTurk, a crowdsourcing platform. Participants indicated their level of openness to using the AI technology in the healthcare scenario. Items reflecting potential concerns and benefits associated with each technology accompanied the scenarios. Participants rated the extent that the statements of concerns and benefits influenced their perception of favorability toward the technology. Participants completed measures of socio-demographics, health variables, and psychosocial variables such as trust in the healthcare system and trust in technology. Exploratory and confirmatory factor analyses of the concern and benefit items identified two factors representing overall level of concern and perceived benefit. Descriptive analyses examined levels of openness, concern, and perceived benefit. Correlational analyses explored associations of socio-demographic, health, and psychosocial variables with openness, concern, and benefit scores while multivariable regression models examined these relationships concurrently. Results Participants were moderately open to AI-driven healthcare technologies (M = 3.1/5.0 ± 0.9), but there was variation depending on the type of application, and the statements of concerns and benefits swayed views. Trust in the healthcare system and trust in technology were the strongest, most consistent correlates of openness, concern, and perceived benefit. Most other socio-demographic, health-related, and psychosocial variables were less strongly, or not, associated, but multivariable models indicated some personality characteristics (e.g., conscientiousness and agreeableness) and socio-demographics (e.g., full-time employment, age, sex, and race) were modestly related to perceptions. Conclusions Participants’ openness appears tenuous, suggesting early promotion strategies and experiences with novel AI technologies may strongly influence views, especially if implementation of AI technologies increases or undermines trust. The exploratory nature of these findings warrants additional research.

Sign in / Sign up

Export Citation Format

Share Document