scholarly journals Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 720
Author(s):  
Masaaki Komatsu ◽  
Akira Sakai ◽  
Ai Dozen ◽  
Kanto Shozu ◽  
Suguru Yasutomi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Clinical Application ◽  
The United States ◽  
Imaging Analysis ◽  
Future Perspectives ◽  
Clinical Implementation ◽  
Global Trends ◽  
Extensive Range ◽  
Image Quality Control ◽  
Diagnostic Support

Artificial intelligence (AI) is being increasingly adopted in medical research and applications. Medical AI devices have continuously been approved by the Food and Drug Administration in the United States and the responsible institutions of other countries. Ultrasound (US) imaging is commonly used in an extensive range of medical fields. However, AI-based US imaging analysis and its clinical implementation have not progressed steadily compared to other medical imaging modalities. The characteristic issues of US imaging owing to its manual operation and acoustic shadows cause difficulties in image quality control. In this review, we would like to introduce the global trends of medical AI research in US imaging from both clinical and basic perspectives. We also discuss US image preprocessing, ingenious algorithms that are suitable for US imaging analysis, AI explainability for obtaining informed consent, the approval process of medical AI devices, and future perspectives towards the clinical application of AI-based US diagnostic support technologies.

scholarly journals Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3532 ◽  
Author(s):  
Ryuji Hamamoto ◽  
Kruthi Suvarna ◽  
Masayoshi Yamada ◽  
Kazuma Kobayashi ◽  
Norio Shinkai ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Precision Medicine ◽  
Medical Devices ◽  
The United States ◽  
Medical Data ◽  
Clinical Implementation ◽  
Medical Field ◽  
Core Technology ◽  
Artificial Intelligence Technology ◽  
History Of

In recent years, advances in artificial intelligence (AI) technology have led to the rapid clinical implementation of devices with AI technology in the medical field. More than 60 AI-equipped medical devices have already been approved by the Food and Drug Administration (FDA) in the United States, and the active introduction of AI technology is considered to be an inevitable trend in the future of medicine. In the field of oncology, clinical applications of medical devices using AI technology are already underway, mainly in radiology, and AI technology is expected to be positioned as an important core technology. In particular, “precision medicine,” a medical treatment that selects the most appropriate treatment for each patient based on a vast amount of medical data such as genome information, has become a worldwide trend; AI technology is expected to be utilized in the process of extracting truly useful information from a large amount of medical data and applying it to diagnosis and treatment. In this review, we would like to introduce the history of AI technology and the current state of medical AI, especially in the oncology field, as well as discuss the possibilities and challenges of AI technology in the medical field.

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.

Global Trends in the Political Economy of Smart Grids

2017 ◽  
Author(s):  
Cherrelle Eid ◽  
Rudi Hakvoort ◽  
Martin de Jong
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
The United States ◽  
Industry Structure ◽  
Electricity Sector ◽  
Distributed Energy ◽  
Global Trends ◽  
Political Economic ◽  
Regulatory Models ◽  
Global Transition

The global transition towards sustainable, secure, and affordable electricity supply is driving changes in the consumption, production, and transportation of electricity. This chapter provides an overview of three main causes of political–economic tensions with smart grids in the United States, Europe, and China, namely industry structure, regulatory models, and the impact of energy policy. In all cases, the developments are motivated by the possible improvements in reliability and affordability yielded by smart grids, while sustainability of the electricity sector is not a central motivation. A holistic smart grid vision would open up possibilities for better integration of distributed energy resources. The authors recommend that smart grid investments should remain outside of the regulatory framework for utilities and distribution service operators in order to allow for such developments.

scholarly journals Artificial intelligence and colonoscopy: Current status and future perspectives

2019 ◽  
Vol 31 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Shin‐ei Kudo ◽  
Yuichi Mori ◽  
Masashi Misawa ◽  
Kenichi Takeda ◽  
Toyoki Kudo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Current Status ◽  
Future Perspectives

scholarly journals 8.I. Workshop: Populist radical right and health: National policies and global trends

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
◽  
Keyword(s):  
Public Health ◽  
United States ◽  
Welfare State ◽  
The United States ◽  
Radical Right ◽  
Health Policies ◽  
National Policies ◽  
Global Trends ◽  
Populist Radical Right ◽  
The Welfare State

Abstract Populist radical right (PRR) parties have been steadily expanding, not only in the number of supporters they gain and the seats they win in governments, but more importantly they have been increasingly elected into governmental coalitions as well as presidential offices. With the prominence of these authoritarian, nationalistic and populist parties, it is often difficult to discern what kind of policies they actually stand for. Particularly with regards to the welfare state and public health, it is not always clear what these parties stand for. At times they call for a reduction of health-related welfare provision, despite the fact that this goes against the will of the “ordinary people”, their core supporters; they often promote radical reductions of welfare benefits among socially excluded groups - usually immigrants, whom are most in need of such services; and finally they often mobilize against evidence-based policies. The purpose of this workshop is to present the PRRs actual involvement in health care and health policies across various countries. As PRR parties increase and develop within but also outside of the European continent it is necessary to keep track of their impact, particularly with regards to health and social policies. Although research surrounding PRR parties has significantly expanded over the last years, their impact on the welfare state and more specifically health policies still remains sparse. This workshop will present findings from the first comprehensive book connecting populist radical right parties with actual health and social policy effects in Europe (Eastern and Western) as well as in the United States. This workshop presents five country cases (Austria, Poland, the Netherlands, the United States) from the book Populist Radical Right and Health: National Policies and Global Trends. All five presentations will address PRR parties or leaders and their influence on health, asking the questions “How influential are PRR parties or leaders when it comes to health policy?” “Do the PRR actually have an impact on policy outcomes?” and “What is the actual impact of the health policies implemented by PRR parties or leaders?” After these five presentations, the participants of the workshop will be engaged in an interactive discussion. Key messages As the number of PRR parties increase worldwide and their involvement in national governments become inevitable, new light must be shed on the impact these political parties have on public health. Politics needs to become better integrated into public health research. The rise of PRR parties in Europe might have serious consequences for public health and needs to be further explored.

scholarly journals AI MSK clinical applications: spine imaging

2021 ◽  
Author(s):  
Florian A. Huber ◽  
Roman Guggenberger
Keyword(s):  
Artificial Intelligence ◽  
Clinical Application ◽  
Value Chain ◽  
Clinical Applications ◽  
Status Quo ◽  
Use Cases ◽  
Musculoskeletal Imaging ◽  
Future Perspective ◽  
Spine Imaging ◽  
The Status

AbstractRecent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain in spine imaging, independent from modality or specific application. This review aims to summarize the status quo and future perspective regarding utilization of AI for spine imaging. First, the basics of AI concepts are clarified. Second, the different tasks and use cases for AI applications in spine imaging are discussed and illustrated by examples. Finally, the authors of this review present their personal perception of AI in daily imaging and discuss future chances and challenges that come along with AI-based solutions.

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.

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