Artificial Intelligence in Self-Driving Cars Research and Innovation: A Scientometric and Bibliometric Analysis

2021 ◽  
Author(s):  
Gianluca Biggi ◽  
Jack Stilgoe
Keyword(s):  
Artificial Intelligence ◽  
Bibliometric Analysis ◽  
Research And Innovation ◽  
Self Driving Cars

Artificial Intelligence in Logistics

2019 ◽  
Vol 12 (1) ◽  
pp. 47-60
Author(s):  
László Kota
Keyword(s):  
Artificial Intelligence ◽  
Computing Power ◽  
Self Driving Cars

The artificial intelligence undergoes an enormous development since its appearance in the fifties. The computing power has grown exponentially since then, enabling the use of artificial intelligence applications in different areas. Since then, artificial intelligence applications are not only present in the industry, but they have slowly conquered households as well. Their use in logistics is becoming more and more widespread, just think of self-driving cars and trucks. In this paper, the author attempts to summarize and present the artificial intelligence logistical applications, its development and impact on logistics.

Top 100 most-cited articles on medical imaging applications of artificial intelligence: a bibliometric analysis (Preprint)

2020 ◽  
Author(s):  
Ying Liu ◽  
Ziyan Yu ◽  
Shuolan Jing ◽  
Honghu Jiang ◽  
Chunxia Wang
Keyword(s):  
Artificial Intelligence ◽  
Medical Imaging ◽  
Bibliometric Analysis ◽  
Clinical Medicine ◽  
Medical Physics ◽  
Medical Image Analysis ◽  
The United States ◽  
Independent Learning ◽  
Learning Ability ◽  
Core Technology

BACKGROUND Artificial intelligence (AI) has penetrated into almost every aspect of our lives and is rapidly changing our way of life. Recently, the new generation of AI taking machine learning and particularly deep convolutional neural network theories as the core technology, has stronger learning ability and independent learning evolution ability, combined with a large amount of learning data, breaks through the bottleneck limit of model accuracy, and makes the model efficient use. OBJECTIVE To identify the 100 most cited papers in artificial intelligence in medical imaging, we performed a comprehensive bibliometric analysis basing on the literature search on Web of Science Core Collection (WoSCC). METHODS The 100 top-cited articles published in “AI, Medical imaging” journals were identified using the Science Citation Index Database. The articles were further reviewed, and basic information was collected, including the number of citations, journals, authors, publication year, and field of study. RESULTS The highly cited articles in AI were cited between 72 and 1,554 times. The majority of them were published in three major journals: IEEE Transactions on Medical Imaging, Medical Image Analysis and Medical Physics. The publication year ranged from 2002 to 2019, with 66% published in a three-year period (2016 to 2018). Publications from the United States (56%) were the most heavily cited, followed by those from China (15%) and Netherlands (10%). Radboud University Nijmegen from Netherlands, Harvard Medical School in USA, and The Chinese University of Hong Kong in China produced the highest number of publications (n=6). Computer science (42%), clinical medicine (35%), and engineering (8%) were the most common fields of study. CONCLUSIONS Citation analysis in the field of artificial intelligence in medical imaging reveals interesting information about the topics and trends negotiated by researchers and elucidates which characteristics are required for a paper to attain a “classic” status. Clinical science articles published in highimpact specialized journals are most likely to be cited in the field of artificial intelligence in medical imaging.

scholarly journals Application of Artificial Intelligence in COVID-19 Pandemic: Bibliometric Analysis

Healthcare ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 441
Author(s):  
Md. Mohaimenul Islam ◽  
Tahmina Nasrin Poly ◽  
Belal Alsinglawi ◽  
Li-Fong Lin ◽  
Shuo-Chen Chien ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Bibliometric Analysis ◽  
English Language ◽  
R Package ◽  
Research Area ◽  
Republic Of China ◽  
Comprehensive Picture ◽  
The Usa ◽  
The Republic ◽  
Academy Of Sciences

The application of artificial intelligence (AI) to health has increased, including to COVID-19. This study aimed to provide a clear overview of COVID-19-related AI publication trends using longitudinal bibliometric analysis. A systematic literature search was conducted on the Web of Science for English language peer-reviewed articles related to AI application to COVID-19. A search strategy was developed to collect relevant articles and extracted bibliographic information (e.g., country, research area, sources, and author). VOSviewer (Leiden University) and Bibliometrix (R package) were used to visualize the co-occurrence networks of authors, sources, countries, institutions, global collaborations, citations, co-citations, and keywords. We included 729 research articles on the application of AI to COVID-19 published between 2020 and 2021. PLOS One (33/729, 4.52%), Chaos Solution Fractals (29/729, 3.97%), and Journal of Medical Internet Research (29/729, 3.97%) were the most common journals publishing these articles. The Republic of China (190/729, 26.06%), the USA (173/729, 23.73%), and India (92/729, 12.62%) were the most prolific countries of origin. The Huazhong University of Science and Technology, Wuhan University, and the Chinese Academy of Sciences were the most productive institutions. This is the first study to show a comprehensive picture of the global efforts to address COVID-19 using AI. The findings of this study also provide insights and research directions for academic researchers, policymakers, and healthcare practitioners who wish to collaborate in these domains in the future.

scholarly journals Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research

2021 ◽  
pp. 155626462110027
Author(s):  
Gabrielle Samuel ◽  
Jenn Chubb ◽  
Gemma Derrick
Keyword(s):  
Artificial Intelligence ◽  
Health Research ◽  
Decision Makers ◽  
Societal Impact ◽  
The Past ◽  
Research And Innovation ◽  
The United Kingdom ◽  
Responsible Research ◽  
Past Half

The governance of ethically acceptable research in higher education institutions has been under scrutiny over the past half a century. Concomitantly, recently, decision makers have required researchers to acknowledge the societal impact of their research, as well as anticipate and respond to ethical dimensions of this societal impact through responsible research and innovation principles. Using artificial intelligence population health research in the United Kingdom and Canada as a case study, we combine a mapping study of journal publications with 18 interviews with researchers to explore how the ethical dimensions associated with this societal impact are incorporated into research agendas. Researchers separated the ethical responsibility of their research with its societal impact. We discuss the implications for both researchers and actors across the Ethics Ecosystem.

The ideological divide in public perceptions of self-driving cars

2020 ◽  
Vol 29 (4) ◽  
pp. 436-451
Author(s):  
Yilang Peng
Keyword(s):  
Artificial Intelligence ◽  
United States ◽  
Scientific Literacy ◽  
Autonomous Vehicles ◽  
The United States ◽  
Public Perceptions ◽  
New Information ◽  
Nationally Representative ◽  
Self Driving Cars ◽  
Social Conservatism

Applications in artificial intelligence such as self-driving cars may profoundly transform our society, yet emerging technologies are frequently faced with suspicion or even hostility. Meanwhile, public opinions about scientific issues are increasingly polarized along the ideological line. By analyzing a nationally representative panel in the United States, we reveal an emerging ideological divide in public reactions to self-driving cars. Compared with liberals and Democrats, conservatives and Republicans express more concern about autonomous vehicles and more support for restrictively regulating autonomous vehicles. This ideological gap is largely driven by social conservatism. Moreover, both familiarity with driverless vehicles and scientific literacy reduce respondents’ concerns over driverless vehicles and support for regulation policies. Still, the effects of familiarity and scientific literacy are weaker among social conservatives, indicating that people may assimilate new information in a biased manner that promotes their worldviews.

scholarly journals An intersectional approach to analyse gender productivity and open access: a bibliometric analysis of the Italian National Research Council

2021 ◽  
Author(s):  
Roberta Ruggieri ◽  
Fabrizio Pecoraro ◽  
Daniela Luzi
Keyword(s):  
Open Access ◽  
Bibliometric Analysis ◽  
Gender Gap ◽  
Research Council ◽  
National Research Council ◽  
Research Area ◽  
Scientific Production ◽  
Italian National Research Council ◽  
European Research ◽  
Research And Innovation

AbstractGender equality and Open Access (OA) are priorities within the European Research Area and cross-cutting issues in European research program H2020. Gender and openness are also key elements of responsible research and innovation. However, despite the common underlying targets of fostering an inclusive, transparent and sustainable research environment, both issues are analysed as independent topics. This paper represents a first exploration of the inter-linkages between gender and OA analysing the scientific production of researchers of the Italian National Research Council under a gender perspective integrated with the different OA publications modes. A bibliometric analysis was carried out for articles published in the period 2016–2018 and retrieved from the Web of Science. Results are presented constantly analysing CNR scientific production in relation to gender, disciplinary fields and OA publication modes. These variables are also used when analysing articles that receive financial support. Our results indicate that gender disparities in scientific production still persist particularly in STEM disciplines, while the gender gap is the closest to parity in medical and agricultural sciences. A positive dynamic toward OA publishing and women’s scientific production is shown when disciplines with well-established open practices are related to articles supported by funds. A slightly higher women’s propensity toward OA is shown when considering Gold OA, or authorships with women in the first and last article by-line position. The prevalence of Italian funded articles with women’s contributions published in Gold OA journals seems to confirm this tendency, especially if considering the weak enforcement of the Italian OA policies.

Assessment of driving quality and its impact on changes in the technical condition of self-driving cars

2020 ◽  
pp. 24-26
Keyword(s):  
Artificial Intelligence ◽  
Life Cycle ◽  
Computer Technology ◽  
Technical Condition ◽  
Entire Life ◽  
Entire Life Cycle ◽  
Machine Maintenance ◽  
Current Task ◽  
Self Driving Cars

The article describes the current task of developing and improving existing technologies for machine maintenance throughout the entire life cycle. The use of modern achievements in the field of computer technology, digitization of information, as well as the development of artificial intelligence technologies, will allow you to get new scientific and engineering results aimed at managing the technical condition of machines in operation.

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