دورية أكاديمية
Bibliometric analysis of artificial intelligence and optical coherence tomography images: research hotspots and frontiers.
| العنوان: | Bibliometric analysis of artificial intelligence and optical coherence tomography images: research hotspots and frontiers. |
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| المؤلفون: | Feng HW; Department of Software Engineering, School of Software, Shenyang University of Technology, Shenyang 110870, Liaoning Province, China., Chen JJ; Department of Software Engineering, School of Software, Shenyang University of Technology, Shenyang 110870, Liaoning Province, China., Zhang ZC; Department of Computer, School of Intelligent Medicine, China Medical University, Shenyang 110122, Liaoning Province, China., Zhang SC; Shenzhen Eye Hospital, Jinan University, Shenzhen 518040, Guangdong Province, China., Yang WH; Shenzhen Eye Hospital, Jinan University, Shenzhen 518040, Guangdong Province, China. |
| المصدر: | International journal of ophthalmology [Int J Ophthalmol] 2023 Sep 18; Vol. 16 (9), pp. 1431-1440. Date of Electronic Publication: 2023 Sep 18 (Print Publication: 2023). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Press of International Journal of Ophthalmology Country of Publication: China NLM ID: 101553860 Publication Model: eCollection Cited Medium: Print ISSN: 2222-3959 (Print) Linking ISSN: 22223959 NLM ISO Abbreviation: Int J Ophthalmol Subsets: PubMed not MEDLINE |
| أسماء مطبوعة: | Original Publication: Xi'an, China : Press of International Journal of Ophthalmology |
| مستخلص: | Aim: To explore the latest application of artificial intelligence (AI) in optical coherence tomography (OCT) images, and to analyze the current research status of AI in OCT, and discuss the future research trend. Methods: On June 1, 2023, a bibliometric analysis of the Web of Science Core Collection was performed in order to explore the utilization of AI in OCT imagery. Key parameters such as papers, countries/regions, citations, databases, organizations, keywords, journal names, and research hotspots were extracted and then visualized employing the VOSviewer and CiteSpace V bibliometric platforms. Results: Fifty-five nations reported studies on AI biotechnology and its application in analyzing OCT images. The United States was the country with the largest number of published papers. Furthermore, 197 institutions worldwide provided published articles, where University of London had more publications than the rest. The reference clusters from the study could be divided into four categories: thickness and eyes, diabetic retinopathy (DR), images and segmentation, and OCT classification. Conclusion: The latest hot topics and future directions in this field are identified, and the dynamic evolution of AI-based OCT imaging are outlined. AI-based OCT imaging holds great potential for revolutionizing clinical care. (International Journal of Ophthalmology Press.) |
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| فهرسة مساهمة: | Keywords: artificial intelligence; bibliometric; deep learning; machine learning; optical coherence tomography |
| تواريخ الأحداث: | Date Created: 20230919 Latest Revision: 20230920 |
| رمز التحديث: | 20231215 |
| مُعرف محوري في PubMed: | PMC10475613 |
| DOI: | 10.18240/ijo.2023.09.09 |
| PMID: | 37724282 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 2222-3959 |
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| DOI: | 10.18240/ijo.2023.09.09 |