scholarly journals Opportunities and challenges of artificial intelligence in the medical field: current application, emerging problems, and problem-solving strategies

2021 ◽  
Vol 49 (3) ◽  
pp. 030006052110001
Author(s):  
Lushun Jiang ◽  
Zhe Wu ◽  
Xiaolan Xu ◽  
Yaqiong Zhan ◽  
Xuehang Jin ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Large Scale ◽  
Medical Industry ◽  
Medical Field ◽  
Current Application ◽  
Brain Science ◽  
Existing Problems ◽  
Design And Implementation ◽  
Process Framework ◽  
Problem Solving Strategies

Recent advancements in the field of artificial intelligence have demonstrated success in a variety of clinical tasks secondary to the development and application of big data, supercomputing, sensor networks, brain science, and other technologies. However, no projects can yet be used on a large scale in real clinical practice because of the lack of standardized processes, lack of ethical and legal supervision, and other issues. We analyzed the existing problems in the field of artificial intelligence and herein propose possible solutions. We call for the establishment of a process framework to ensure the safety and orderly development of artificial intelligence in the medical industry. This will facilitate the design and implementation of artificial intelligence products, promote better management via regulatory authorities, and ensure that reliable and safe artificial intelligence products are selected for application.

scholarly journals An Evaluation of Chinese Human-Computer Dialogue Technology

2019 ◽  
Vol 1 (2) ◽  
pp. 187-200
Author(s):  
Zhengyu Zhao ◽  
Weinan Zhang ◽  
Wanxiang Che ◽  
Zhigang Chen ◽  
Yibo Zhang
Keyword(s):  
Artificial Intelligence ◽  
Large Scale ◽  
Data Sets ◽  
Dialogue Systems ◽  
Online Testing ◽  
User Intent ◽  
Existing Problems ◽  
Intelligent Processing ◽  
Task Oriented ◽  
Important Branch

The human-computer dialogue has recently attracted extensive attention from both academia and industry as an important branch in the field of artificial intelligence (AI). However, there are few studies on the evaluation of large-scale Chinese human-computer dialogue systems. In this paper, we introduce the Second Evaluation of Chinese Human-Computer Dialogue Technology, which focuses on the identification of a user's intents and intelligent processing of intent words. The Evaluation consists of user intent classification (Task 1) and online testing of task-oriented dialogues (Task 2), the data sets of which are provided by iFLYTEK Corporation. The evaluation tasks and data sets are introduced in detail, and meanwhile, the evaluation results and the existing problems in the evaluation are discussed.

scholarly journals Budget Funding Priorities and Development Prospects of the US Artificial Intelligence

2021 ◽  
pp. 65-93
Author(s):  
Y. Selyanin
Keyword(s):  
Artificial Intelligence ◽  
National Security ◽  
Department Of Defense ◽  
Large Scale ◽  
Political Leadership ◽  
Intelligence Community ◽  
Existing Problems ◽  
The Us ◽  
Us Government ◽  
Development Prospects

The US Government has initiated a large-scale activity on artificial intelligence (AI) development and implementation. Numerous departments and agencies including the Pentagon, intelligence community and citizen agencies take part in these efforts. Some of them are responsible for technology, materials and standards development. Others are customers of AI. State AI efforts receive significant budget funding. Moreover, Department of Defense costs on AI are comparable with the whole non-defense funding. American world-leading IT companies support state departments and agencies in organizing AI technologies development and implementation. The USA's highest military and political leadership supports such efforts. Congress provides significant requested funding. However leading specialists criticize the state's approach to creating and implementing AI. Firstly, they consider authorized assignments as not sufficient. Secondly, even this funding is used ineffectively. Therefore Congress created National Security Commission on Artificial Intelligence (NSCAI) in 2018 for identifying problems in the AI area and developing solutions. This article looks at the stakeholders and participants of the state AI efforts, the budget funding authorization, the major existing problems and the NSCAI conclusions regarding the necessary AI funding in FYs 2021-2032.

TO THE PROBLEMS OF COMBATING CORRUPTION IN MODERN RUSSIA AND INTERNATIONAL COOPERATION IN THE FIELD OF ANTI-CORRUPTION

2020 ◽  
Author(s):  
Angela Dranishnikova
Keyword(s):  
Large Scale ◽  
The State ◽  
Point Of View ◽  
Modern Life ◽  
Existing Problems ◽  
Moral Point ◽  
Material Goods ◽  
The Russian Federation ◽  
The Difference ◽  
The Government

In the article, the author reflects the existing problems of the fight against corruption in the Russian Federation. He focuses on the opacity of the work of state bodies, leading to an increase in bribery and corruption. The topic we have chosen is socially exciting in our days, since its significance is growing on a large scale at all levels of the investigated aspect of our modern life. Democratic institutions are being jeopardized, the difference in the position of social strata of society in society’s access to material goods is growing, and the state of society is suffering from the moral point of view, citizens are losing confidence in the government, and in the top officials of the state.

Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey (Preprint)

2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Online Survey ◽  
Medical Professionals ◽  
Medical Field ◽  
Acceptance Level ◽  
Professional Workers ◽  
Basic Understanding ◽  
Comparative Survey ◽  
Definition Of

BACKGROUND Artificial intelligence (AI) is widely applied in the medical field, especially in ophthalmology. In the development of ophthalmic artificial intelligence, some problems worthy of attention have gradually emerged, among which the ophthalmic AI-related recognition issues are particularly prominent. That is to say, currently, there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. OBJECTIVE This survey aims to assess medical workers’ and other professional technicians’ familiarity with AI, as well as their attitudes toward and concerns of ophthalmic AI. METHODS An electronic questionnaire was designed through the Questionnaire Star APP, an online survey software and questionnaire tool, and was sent to relevant professional workers through Wechat, China’s version of Facebook or WhatsApp. The participation was based on a voluntary and anonymous principle. The questionnaire mainly consisted of four parts, namely the participant’s background, the participant's basic understanding of AI, the participant's attitude toward AI, and the participant's concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS A total of 562 professional workers completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 37.9% of the participants understood AI, and 31.67% understood ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that ophthalmic AI would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with ophthalmic AI application experiences (30.6%), respectively about 84.25% of medical professionals and 73.33% of other professional technicians held a full acceptance attitude toward ophthalmic AI. The participants expressed concerns that ophthalmic AI might bring about issues such as the unclear definition of medical responsibilities, the difficulty of ensuring service quality, and the medical ethics risks. And among the medical workers and other professional technicians who understood ophthalmic AI, 98.39%, and 95.24%, respectively, said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS Analysis of the questionnaire results shows that the medical workers have a higher understanding level of ophthalmic AI than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI, but generally had a relatively high acceptance level of ophthalmic AI, believing that doctors would partly be replaced by it and that there was a need to strengthen research into medical ethics issues of the field.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

scholarly journals Using process data to understand problem-solving strategies and processes for drag-and-drop items in a large-scale mathematics assessment

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Yang Jiang ◽  
Tao Gong ◽  
Luis E. Saldivia ◽  
Gabrielle Cayton-Hodges ◽  
Christopher Agard
Keyword(s):  
Problem Solving ◽  
Time Allocation ◽  
Large Scale ◽  
Solution Process ◽  
Process Data ◽  
Mathematics Assessments ◽  
Assessment Design ◽  
Eighth Grade Students ◽  
Problem Solving Strategies ◽  
Drag And Drop

AbstractIn 2017, the mathematics assessments that are part of the National Assessment of Educational Progress (NAEP) program underwent a transformation shifting the administration from paper-and-pencil formats to digitally-based assessments (DBA). This shift introduced new interactive item types that bring rich process data and tremendous opportunities to study the cognitive and behavioral processes that underlie test-takers’ performances in ways that are not otherwise possible with the response data alone. In this exploratory study, we investigated the problem-solving processes and strategies applied by the nation’s fourth and eighth graders by analyzing the process data collected during their interactions with two technology-enhanced drag-and-drop items (one item for each grade) included in the first digital operational administration of the NAEP’s mathematics assessments. Results from this research revealed how test-takers who achieved different levels of accuracy on the items engaged in various cognitive and metacognitive processes (e.g., in terms of their time allocation, answer change behaviors, and problem-solving strategies), providing insights into the common mathematical misconceptions that fourth- and eighth-grade students held and the steps where they may have struggled during their solution process. Implications of the findings for educational assessment design and limitations of this research are also discussed.

Humans in Large-scale, Networked Virtual Environments

1997 ◽  
Vol 6 (5) ◽  
pp. 547-564 ◽  
Author(s):  
David R. Pratt ◽  
Shirley M. Pratt ◽  
Paul T. Barham ◽  
Randall E. Barker ◽  
Marianne S. Waldrop ◽  
...  
Keyword(s):  
Virtual Environments ◽  
Large Scale ◽  
Group Representations ◽  
Networked Virtual Environments ◽  
Existing Problems ◽  
Body Tracking ◽  
Level Of Details ◽  
New Ideas ◽  
Work Done ◽  
Tracking Technology

This paper examines the representation of humans in large-scale, networked virtual environments. Previous work done in this field is summarized, and existing problems with rendering, articulating, and networking numerous human figures in real time are explained. We have developed a system that integrates together some well-known solutions along with new ideas. Models with multiple level of details, body-tracking technology and animation libraries to specify joint angles, efficient group representations to describe multiple humans, and hierarchical network protocols have been successfully employed to increase the number of humans represented, system performance, and user interactivity. The resulting system immerses participants effectively and has numerous useful applications.

Recent Patents on Third Generation Bearing Testing Machine

2021 ◽  
Vol 15 ◽  
Author(s):  
Yanling Zhao ◽  
Huanqing Zhang
Keyword(s):  
Large Scale ◽  
High Efficiency ◽  
Testing Machine ◽  
Theoretical Research ◽  
Third Generation ◽  
Existing Problems ◽  
Military Equipment ◽  
Bearing Life ◽  
The Future ◽  
Testing Technology

Background: Bearing testing machine is the key equipment for bearing design, theoretical research and improvement, and it plays an important role in the performance of bearing life, fatigue, vibration and working temperature. With the requirements of aerospace, military equipment, automobile manufacturing and other industrial fields of the bearing are becoming higher and higher. There is an urgent need for high-precision and high-efficiency bearing testing machines to monitor and analyze the performance of bearings. Objective: By analyzing the recent patents, the characteristics and existing problems of the current bearing testing machine are summarized to provide references for the development of bearing test equipment in the future. Methods: This paper reviews various representative patents related to the third generation bearing testing machines. Results: Although the structure of bearing testing machines is different, the main problems in the structure and design principle of bearing testing machine have been summarized and analyzed, and the development of trend and direction of the future bearing testing machine have been discussed. Conclusion: Bearing testing machines for health monitoring of bearing life cycle is of great significance. The current bearing testing machine has basically achieved the monitoring and analysis However, due to the emergence of new types of bearings, further improvement is still needed. With the development of testing technology towards intelligent and big data-driven direction, bearing testing machine is moving towards the type of cloud computing and large-scale testing.

Prospects for Cooperation Between Russia and the Republic of Korea in the Fields of Big Data, Network and Artificial Intelligence for the Development of the Digital Economy

2021 ◽  
Vol 65 (8) ◽  
pp. 51-60
Author(s):  
Yujeong Kim
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Large Scale ◽  
Technology Development ◽  
Technological Development ◽  
Digital Economy ◽  
Republic Of Korea ◽  
Data Network ◽  
Leading Position ◽  
The Government

Today, each country has interest in digital economy and has established and implemented policies aimed at digital technology development and digital transformation for the transition to the digital economy. In particular, interest in digital technologies such as big data, 5G, and artificial intelligence, which are recognized as important factors in the digital economy, has been increasing recently, and it is a time when the role of the government for technological development and international cooperation becomes important. In addition to the overall digital economic policy, the Russian and Korean governments are also trying to improve their international competitiveness and take a leading position in the new economic order by establishing related technical and industrial policies. Moreover, Republic of Korea often refers to data, network and artificial intelligence as D∙N∙A, and has established policies in each of these areas in 2019. Russia is also establishing and implementing policies in the same field in 2019. Therefore, it is timely to find ways to expand cooperation between Russia and Republic of Korea. In particular, the years of 2020and 2021marks the 30th anniversary of diplomatic relations between the two countries, and not only large-scale events and exchange programs have prepared, but the relationship is deepening as part of the continued foreign policy of both countries – Russia’s Eastern Policy and New Northern Policy of Republic of Korea. Therefore, this paper compares and analyzes the policies of the two countries in big data, 5G, and artificial intelligence to seek long-term sustainable cooperation in the digital economy.

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