Artificial intelligence for diabetic retinopathy

Li, Sicong; Zhao, Ran; Zou, Haidong

doi:10.1097/cm9.0000000000001816

Cited by 19 publications

(10 citation statements)

References 64 publications

(91 reference statements)

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“…In addition, based on the new data to intelligently identify and predict the data [ 8 , 9 ], artificial intelligence technology is the most representative technological innovation in the new round of technological progress. AI has four major economic effects, namely, the intelligent penetration effect, the boundary extension effect, the knowledge creation effect, and the self-deepening effect [ 10 ]. With the development of artificial intelligence, through the original mechanical equipment embedded intelligent system, the transformation level rises, forming a series of intelligent machines, equipment interconnection, and data exchange and processes for each industry combination.…”

Section: Methods For the Integrated Development Of Artificial Intelli...mentioning

confidence: 99%

“…Computational Intelligence and Neuroscience [10]. With the development of artifcial intelligence, through the original mechanical equipment embedded intelligent system, the transformation level rises, forming a series of intelligent machines, equipment interconnection, and data exchange and processes for each industry combination.…”

Section: Artifcial Intelligence Technology and Economicmentioning

confidence: 99%

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Integrated Development of Artificial Intelligence and Economic Management

He¹,

Ding²

2022

Computational Intelligence and Neuroscience

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The world economy is developing rapidly. Behind the rapid development, the management of economic regions is very important. In the process of economic management, the government plays the role of macrocontrol and is responsible for the management of various economic affairs and social and economic services. While undertaking infrastructure construction, it creates a good environment for economic development. However, with the deepening of economic development and the more and more complex economic data, the current economic management has gradually exposed a range of issues that arise during the process of economic development, and these problems need to be solved urgently. At this time, the application scope of artificial intelligence in the economic field is getting wider and wider, and it has a great positive effect on economic development. Therefore, in order to solve the problem of economic management in the process of economic development, this paper proposes a development path that integrates AI and economic management and provides intelligent technology support for the development of economic management to help the smooth operation of economic development. In addition, this paper shows through experiments that the path of integration of AI and economic management can promote the development and smooth operation of the economy, and AI has a positive impact on economic management.

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Section: Methods For the Integrated Development Of Artificial Intelli...mentioning

confidence: 99%

Section: Artifcial Intelligence Technology and Economicmentioning

confidence: 99%

Integrated Development of Artificial Intelligence and Economic Management

He¹,

Ding²

2022

Computational Intelligence and Neuroscience

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“…In 2017, Ting, DSW and others obtained high sensitivity and specificity when using the deep learning system to evaluate the diagnostic images of patients with diabetes retinopathy and related eye diseases from multiple ethnic groups ( Ting et al, 2017 ). Li, SC and others pointed out that the conditions for using artificial intelligence system to replace ophthalmologists are not mature ( Li et al, 2022 ). Therefore, using AI technology to diagnose diabetes retinopathy or other ophthalmic diseases requires more research.…”

Section: Discussionmentioning

confidence: 99%

Systematic Bibliometric and Visualized Analysis of Research Hotspots and Trends on the Application of Artificial Intelligence in Ophthalmic Disease Diagnosis

Zhao

Zhu

et al. 2022

Front. Pharmacol.

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Background: Artificial intelligence (AI) has been used in the research of ophthalmic disease diagnosis, and it may have an impact on medical and ophthalmic practice in the future. This study explores the general application and research frontier of artificial intelligence in ophthalmic disease detection.Methods: Citation data were downloaded from the Web of Science Core Collection database to evaluate the extent of the application of Artificial intelligence in ophthalmic disease diagnosis in publications from 1 January 2012, to 31 December 2021. This information was analyzed using CiteSpace.5.8. R3 and Vosviewer.Results: A total of 1,498 publications from 95 areas were examined, of which the United States was determined to be the most influential country in this research field. The largest cluster labeled “Brownian motion” was used prior to the application of AI for ophthalmic diagnosis from 2007 to 2017, and was an active topic during this period. The burst keywords in the period from 2020 to 2021 were system, disease, and model.Conclusion: The focus of artificial intelligence research in ophthalmic disease diagnosis has transitioned from the development of AI algorithms and the analysis of abnormal eye physiological structure to the investigation of more mature ophthalmic disease diagnosis systems. However, there is a need for further studies in ophthalmology and computer engineering.

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“…The training set is to train the algorithm, the validation set is used for parameter selection and tuning, and the testing set is used to evaluate the actual performance of the AI system in clinical scenarios. [10] [Figure 1] shows how a normal AI process works.…”

Section: Ai Algorithm Development For Drmentioning

confidence: 99%

Using artificial intelligence in diabetic retinopathy

Mohan

Gaur

Raman

2022

IHOPEJO

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Diabetic retinopathy (DR), a microvascular complication of diabetes, is a leading cause of blindness in India. Regular and timely screening for DR is recommended for the early diagnosis and appropriate treatment. However, mass screening for DR poses a significant challenge. Artificial intelligence (AI) is an important tool which has been used for diagnosing and grading diabetic retinopathy and aids in mass DR screening thus helping in faster and earlier screening of DR. This article aims to describe how AI is used in DR, software that are available for screening and the limitations and challenges in implementation of AI in health-care settings.

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Artificial intelligence for diabetic retinopathy

Cited by 19 publications

References 64 publications

Integrated Development of Artificial Intelligence and Economic Management

Integrated Development of Artificial Intelligence and Economic Management

Systematic Bibliometric and Visualized Analysis of Research Hotspots and Trends on the Application of Artificial Intelligence in Ophthalmic Disease Diagnosis

Using artificial intelligence in diabetic retinopathy

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