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.

scholarly journals Application of Artificial Intelligence Technology in Mechanical Electrical Control System

2021 ◽  
Vol 2066 (1) ◽  
pp. 012057
Author(s):  
Nan Li
Keyword(s):  
Artificial Intelligence ◽  
Control System ◽  
Control Systems ◽  
Current Status ◽  
Work Efficiency ◽  
Electrical Control ◽  
Existing Problems ◽  
The Core ◽  
Core Technology ◽  
Artificial Intelligence Technology

Abstract Artificial intelligence technology (A I T) has also been widely used in society. Combining A I T with mechanical and electrical control systems will bring huge profits to the corporate sector and greatly improve work efficiency. It can save a lot of money in the electrical control operations of all walks of life in the country, and fill the gap in this technology in the country. The purpose of this article is to study the application of A I T in mechanical electrical control systems (M E C S). This article first introduces the basic theories and concepts of A I T, extends the core technology of A I T, and combines the current status of the electrical control system of modern enterprises in our country to discuss its existing problems, and finally studies and analyzes A I T and machinery. Combination of electrical control systems, and discuss the application of A I T in mechanical electrical orifice subsystems. Experiments show that, compared with the existing M E C S, the M E C S using A I T can better complete the work and improve work efficiency.

scholarly journals Smart Technology and Industry Trends in Fourth Industrial Revolution

2019 ◽  
Vol 8 (2S6) ◽  
pp. 400-404
Keyword(s):  
Artificial Intelligence ◽  
Autonomous Vehicles ◽  
Industrial Revolution ◽  
Unmanned Vehicles ◽  
Core Technology ◽  
Artificial Intelligence Technology ◽  
Technical Factors ◽  
Smart Machine ◽  
Industry Trends ◽  
Technology Trends

In this paper, we have been studying the technology trends closely approaching us and the smart machine, which is a representative example of the forth industrial revolution. The key content in technology trends is artificial intelligence. Artificial intelligence technology is being used as a core technology of the 4th industrial revolution. In autonomous vehicles, which are representative industries, artificial intelligence-based unmanned vehicles are emerging, and on the other side, and various voice recognition based products are emerging. In this paper, we have studied the latest technical factors of autonomous automobile and speech recognition based industry, which is a representative industry of the 4th industrial revolution

scholarly journals Risk Management in the Construction of Intelligent Transportation Platform Based on Artificial Intelligence

CONVERTER ◽  
2021 ◽  
pp. 543-549
Author(s):  
Hongxi Di
Keyword(s):  
Artificial Intelligence ◽  
Risk Management ◽  
Traffic Management ◽  
Motor Vehicle ◽  
Transmission Rate ◽  
Intelligent Transportation ◽  
Existing Problems ◽  
Core Technology ◽  
Artificial Intelligence Technology ◽  
Response Measures

The smoothness of a city's traffic is one of the signs that measure the development of a city. With the advent of the era of artificial intelligence and big data, the previously bloated and blocked motor vehicle transportation system is increasingly unable to adapt to this fast-paced society. The use of artificial intelligence technology to build a brand-new intelligent transportation platform is imminent, and reasonable planning of the risks in the construction of the transportation platform can effectively increase the transmission rate and reduce the frequency of accidents. The purpose of this paper is to study the risk management in the construction of intelligent transportation platform based on artificial intelligence. This article first summarizes the basic theory of artificial intelligence, and then extends the core technology of artificial intelligence. And combined with the current situation of my country's contemporary intelligent transportation, analysis of the existing problems and shortcomings, on this basis, combined with artificial intelligence technology to research and analyze the risk management in the construction of intelligent transportation platform. This research systematically expounds the risk construction principles, model construction and risk response measures of the intelligent transportation platform. This paper uses field surveys, interviews and other research methods to research and investigate traffic risk management in a certain place. The experimental research shows that risk management in the construction of intelligent transportation platforms based on artificial intelligence has higher feasibility than traditional traffic management.

Ethical aspects of using software with artificial intelligence technology

2021 ◽  
Vol 20 (1) ◽  
pp. 70-84
Author(s):  
A. L. Khokhlov ◽  
D. Yu. Belousov
Keyword(s):  
Artificial Intelligence ◽  
Clinical Trials ◽  
Social Problems ◽  
Ethics Committee ◽  
Ethical Principles ◽  
Legal Basis ◽  
Ethical Aspects ◽  
Conceptual Apparatus ◽  
Artificial Intelligence Technology ◽  
History Of

Today, artificial intelligence (AI) technologies can offer solutions to many social problems, including those used to diagnose and treat diseases. However, for this it is necessary to provide an appropriate legal basis. The article presents a brief history of the development of AI, explains the conceptual apparatus, describes the legal basis for its development and implementation in Russian healthcare, the methodology for conducting clinical trials of AI systems, and gives their classification. Particular attention is paid to the ethical principles of clinical trials of AI systems. The ethical examination of projects of clinical trials of AI systems by the Ethics Committee is considered in detail.

scholarly journals Research on Integrated Development Technology of Artificial Intelligence, Big Data and Cloud Computing

2021 ◽  
pp. 349-356
Author(s):  
Yu Qing
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Development Strategy ◽  
Reference Value ◽  
The United States ◽  
Two Dimensions ◽  
Integrated Development ◽  
Development Technology ◽  
Artificial Intelligence Technology

Big data is profoundly changing our society and our way of production, life and thinking. At the same time, the development of big data continues to promote the innovation and breakthrough of artificial intelligence. Artificial intelligence is the focus of current research. All countries also raise artificial intelligence to the national strategic level and seize the commanding height of artificial intelligence. This paper analyzes the strategic characteristics of the development of artificial intelligence in the United States, Britain and Japan from the two dimensions of technology deployment and system guarantee. This paper studies the artificial intelligence technology based on big data and the development strategy of artificial intelligence, so as to provide a strategic idea for the development of artificial intelligence in China. The idea has a certain reference value for the research on the integrated development technology of artificial intelligence, big data and cloud computing.

scholarly journals In Search of a Unifying Concept in Human Diseases

Diseases ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 68
Author(s):  
James Trosko
Keyword(s):  
Artificial Intelligence ◽  
Precision Medicine ◽  
New Technologies ◽  
Genome Project ◽  
Human Diseases ◽  
Therapeutic Benefits ◽  
History Of ◽  
Biological Discovery ◽  
Definition Of ◽  
The Human Genome Project

Throughout the history of biological/medicine sciences, there has been opposing strategies to find solutions to complex human disease problems. Both empirical and deductive approaches have led to major insights and concepts that have led to practical preventive and therapeutic benefits for the human population. The classic definitions of “science” (to know) has been paired with the classic definition of technology (to do). One knew more as the technology developed, and that development was often based on science. In other words, one could do more if science could improve the technology. In turn, this made possible to know more science with improved technology. However, with the development of new technologies of today in biology and medicine, major advances have been made, such as the information from the Human Genome Project, genetic engineering techniques and the use of bioinformatic uses of sophisticated computer analyses. This has led to the renewed idea that Precision Medicine, while raising some serious ethical concerns, also raises the expectation of improved potential of risk predictions for prevention and treatment of various genetically and environmentally influenced human diseases. This new field Artificial Intelligence, as a major handmaiden to Precision Medicine, is significantly altering the fundamental means of biological discovery. However, can today’s fundamental premise of “Artificial Intelligence”, based on identifying DNA, as the primary nexus of human health and disease, provide the practical solutions to complex human diseases that involve the interaction of those genes with the broad spectrum of “environmental factors”? Will it be “precise” enough to provide practical solutions for prevention and treatments of diseases? In this “Commentary”, with the example of human carcinogenesis, it will be challenged that, without the integration of mechanistic and hypothesis-driven approaches with the “unbiased” empirical analyses of large numbers of data, the Artificial Intelligence approach with fall short.

Electronic Medical Devices; A Primer for Pathologists

2003 ◽  
Vol 127 (7) ◽  
pp. 814-825 ◽  
Author(s):  
James B. Weitzman
Keyword(s):  
Medical Devices ◽  
Product Information ◽  
Data Extraction ◽  
The United States ◽  
Reporting Guidelines ◽  
Cardiac Pacemakers ◽  
Surgical Specimen ◽  
Study Selection ◽  
Potential Applications ◽  
History Of

Abstract Context.—Electronic medical devices (EMDs) with downloadable memories, such as implantable cardiac pacemakers, defibrillators, drug pumps, insulin pumps, and glucose monitors, are now an integral part of routine medical practice in the United States, and functional organ replacements, such as the artificial heart, pancreas, and retina, will most likely become commonplace in the near future. Often, EMDs end up in the hands of the pathologist as a surgical specimen or at autopsy. No established guidelines for systematic examination and reporting or comprehensive reviews of EMDs currently exist for the pathologist. Objective.—To provide pathologists with a general overview of EMDs, including a brief history; epidemiology; essential technical aspects, indications, contraindications, and complications of selected devices; potential applications in pathology; relevant government regulations; and suggested examination and reporting guidelines. Data Sources.—Articles indexed on PubMed of the National Library of Medicine, various medical and history of medicine textbooks, US Food and Drug Administration publications and product information, and specifications provided by device manufacturers. Study Selection.—Studies were selected on the basis of relevance to the study objectives. Data Extraction.—Descriptive data were selected by the author. Data Synthesis.—Suggested examination and reporting guidelines for EMDs received as surgical specimens and retrieved at autopsy. Conclusions.—Electronic medical devices received as surgical specimens and retrieved at autopsy are increasing in number and level of sophistication. They should be systematically examined and reported, should have electronic memories downloaded when indicated, will help pathologists answer more questions with greater certainty, and should become an integral part of the formal knowledge base, research focus, training, and practice of pathology.

Globalizing the Scientific Bandwagon: Trajectories of Precision Medicine in China and Brazil

2020 ◽  
Vol 46 (1) ◽  
pp. 192-225 ◽  
Author(s):  
Larry Au ◽  
Renan Gonçalves Leonel da Silva
Keyword(s):  
Precision Medicine ◽  
Large Scale ◽  
Dynamic Network ◽  
The United States ◽  
Biomedical Sciences ◽  
Biomedical Knowledge ◽  
Strong State ◽  
Institutional Void ◽  
History Of ◽  
Private Actors

Precision medicine (PM) is emerging as a scientific bandwagon within the contemporary biomedical sciences in the United States. PM brings together concepts and tools from genomics and bioinformatics to develop better diagnostics and therapies based on individualized information. Developing countries like China and Brazil have also begun pursuing PM projects, motivated by a desire to claim genomic sovereignty over its population. In spite of commonalities, institutional arrangements produced by the history of genomics research in China and Brazil are ushering PM along different trajectories. In the Chinese case, we identify a strong state-backed push for PM combined with a dynamic network of international academic and private actors along the lines of networked technonationalism that has made large-scale, speculative PM projects possible. The Brazilian case is characterized by an institutional void at the federal level in which PM is driven by domestic academic actors in universities in the regional level, resulting in smaller scale, needs-driven PM projects. Through these cases, this paper shows how a scientific bandwagon adapts to national histories and institutions. Through this peripheral translation of the scientific bandwagon, the global infrastructure of biomedical knowledge has the potential to be transformed.

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