Artificial intelligence in cardiovascular CT: Current status and future implications

2021 ◽  
Author(s):  
Andrew Lin ◽  
Márton Kolossváry ◽  
Manish Motwani ◽  
Ivana Išgum ◽  
Pál Maurovich-Horvat ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Current Status ◽  
Cardiovascular Ct

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

Artificial intelligence in upper GI endoscopy ‐ current status, challenges and future promise

2021 ◽  
Vol 36 (1) ◽  
pp. 20-24
Author(s):  
Honggang Yu ◽  
Rajvinder Singh ◽  
Seon Ho Shin ◽  
Khek Yu Ho
Keyword(s):  
Artificial Intelligence ◽  
Current Status ◽  
Gi Endoscopy ◽  
Upper Gi ◽  
Upper Gi Endoscopy

Reinforcement Learning for Cloud Computing Digital Library

2014 ◽  
Vol 571-572 ◽  
pp. 105-108
Author(s):  
Lin Xu
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Reinforcement Learning ◽  
Digital Library ◽  
Learning Algorithms ◽  
Experimental Results ◽  
Current Status ◽  
Self Learning ◽  
New Framework

This paper proposes a new framework of combining reinforcement learning with cloud computing digital library. Unified self-learning algorithms, which includes reinforcement learning, artificial intelligence and etc, have led to many essential advances. Given the current status of highly-available models, analysts urgently desire the deployment of write-ahead logging. In this paper we examine how DNS can be applied to the investigation of superblocks, and introduce the reinforcement learning to improve the quality of current cloud computing digital library. The experimental results show that the method works more efficiency.

Artificial intelligence and ophthalmology: Current status

2021 ◽  
Vol 96 (8) ◽  
pp. 399-400
Author(s):  
J. Zarranz-Ventura ◽  
C. Bernal-Morales ◽  
M. Saenz de Viteri ◽  
F.J. Castro Alonso ◽  
J.A. Urcola
Keyword(s):  
Artificial Intelligence ◽  
Current Status

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 Application of Artificial Intelligence in Early Gastric Cancer Diagnosis

Digestion ◽  
2021 ◽  
pp. 1-7
Author(s):  
Zili Xiao ◽  
Danian Ji ◽  
Feng Li ◽  
Zhengliang Li ◽  
Zhijun Bao
Keyword(s):  
Artificial Intelligence ◽  
Gastric Cancer ◽  
New Technologies ◽  
Narrow Band Imaging ◽  
Daily Practice ◽  
Colorectal Polyps ◽  
Current Status ◽  
Randomized Controlled ◽  
Depth Prediction ◽  
Substantial Effort

<b><i>Background:</i></b> With the development of new technologies such as magnifying endoscopy with narrow band imaging, endoscopists achieved better accuracy for diagnosis of gastric cancer (GC) in various aspects. However, to master such skill takes substantial effort and could be difficult for inexperienced doctors. Therefore, a novel diagnostic method based on artificial intelligence (AI) was developed and its effectiveness was confirmed in many studies. AI system using convolutional neural network has showed marvelous results in the ongoing trials of computer-aided detection of colorectal polyps. <b><i>Summary:</i></b> With AI’s efficient computational power and learning capacities, endoscopists could improve their diagnostic accuracy and avoid the overlooking or over-diagnosis of gastric neoplasm. Several systems have been reported to achieved decent accuracy. Thus, AI-assisted endoscopy showed great potential on more accurate and sensitive ways for early detection, differentiation, and invasion depth prediction of gastric lesions. However, the feasibility, effectiveness, and safety in daily practice remain to be tested. <b><i>Key messages:</i></b> This review summarizes the current status of different AI applications in early GC diagnosis. More randomized controlled trails will be needed before AI could be widely put into clinical practice.

scholarly journals Research on the Application Mode of Green Environment Design under the Background of Artificial Intelligence

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Hui Liu ◽  
Guanghui Song ◽  
Linlin Yan
Keyword(s):  
Artificial Intelligence ◽  
Process Analysis ◽  
Current Status ◽  
Design System ◽  
Environment Design ◽  
Application Model ◽  
Study Results ◽  
Application Mode ◽  
Design Function ◽  
And Function

In the field of green environmental design, the design system of environmental art is a complex and multidimensional cross-domain fusion system, which can be regarded as a large task system. The development model that combines artificial intelligence (AI) technology and green environment design can not only integrate and analyze problems quickly and efficiently but also provide designers with new design ideas, gradually extending traditional environment design concepts, producing more diverse artistic creation methods, and shifting from a fixed application model to a more diversified artistic development. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of green environment design, elaborated the development background, current status, and future challenges of AI technology, introduced the network topology and platform frame structures of green environment design under the AI background, constructed a technical framework of green environment design under the AI background, analyzed the methods and principles of program design and function development, proposed the application model of green environment design under the AI background, conducted design function model optimization and intelligent design process analysis, and finally discussed the evaluation indicators and hierarchical analysis of the green environment design under the AI background. The results show that the application mode of combining AI technology and green environment design can not only help designers break through traditional time and space barriers and use multidimensional thinking but also help designers have a new understanding of artistic design concept and give full play to the advantages of artificial intelligence in a green environment. The study results of this paper provide a reference for further research on the application mode of green environment design under the AI background.

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