Research hotspots and trends of artificial intelligence in rheumatoid arthritis: A bibliometric and visualized study
-
Published:2023
Issue:12
Volume:20
Page:20405-20421
-
ISSN:1551-0018
-
Container-title:Mathematical Biosciences and Engineering
-
language:
-
Short-container-title:MBE
Author:
Zhang Di1, Fan Bing1, Lv Liu2, Li Da1, Yang Huijun3, Jiang Ping1, Jin Fangmei3
Affiliation:
1. Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan 250011, China 2. Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, China 3. Gansu Provincial Hospital of TCM, Lanzhou 730050, China
Abstract
<abstract>
<p>Artificial intelligence (AI) applications on rheumatoid arthritis (RA) are becoming increasingly popular. In this bibliometric study, we aimed to analyze the characteristics of publications relevant to the research of AI in RA, thereby developing a thorough overview of this research topic. Web of Science was used to retrieve publications on the application of AI in RA from 2003 to 2022. Bibliometric analysis and visualization were performed using Microsoft Excel (2019), R software (4.2.2) and VOSviewer (1.6.18). The overall distribution of yearly outputs, leading countries, top institutions and authors, active journals, co-cited references and keywords were analyzed. A total of 859 relevant articles were identified in the Web of Science with an increasing trend. USA and China were the leading countries in this field, accounting for 71.59% of publications in total. Harvard University was the most influential institution. Arthritis Research & Therapy was the most active journal. Primary topics in this field focused on estimating the risk of developing RA, diagnosing RA using sensor, clinical, imaging and omics data, identifying the phenotype of RA patients using electronic health records, predicting treatment response, tracking the progression of the disease and predicting prognosis and developing new drugs. Machine learning and deep learning algorithms were the recent research hotspots and trends in this field. AI has potential applications in various fields of RA, including the risk assessment, screening, early diagnosis, monitoring, prognosis determination, achieving optimal therapeutic outcomes and new drug development for RA patients. Incorporating machine learning and deep learning algorithms into real-world clinical practice will be a future research hotspot and trend for AI in RA. Extensive collaboration to improve model maturity and robustness will be a critical step in the advancement of AI in healthcare.</p>
</abstract>
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine
Reference50 articles.
1. A. N. Ramesh, C. Kambhampati, J. R. Monson, P. J. Drew, Artificial intelligence in medicine, Ann. R. Coll. Surg. Engl., 86 (2004), 334-338. https://doi.org/10.1308/147870804290 2. H. C. Shin, H. R. Roth, M. Gao, L. Lu, Z. Xu, I. Nogues, et al., Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning, IEEE Trans. Med. Imaging., 35 (2016), 1285-1298. https://doi.org/10.1109/TMI.2016.2528162 3. Y. Mintz, R. Brodie, Introduction to artificial intelligence in medicine, Minim. Invasive Ther. Allied. Technol., 28 (2019), 73-81. https://doi.org/10.1080/13645706.2019.1575882 4. K. Benke, G. Benke, Artificial intelligence and big data in public health, Int. J. Environ. Res. Public Health, 15 (2018), 2796. https://doi.org/10.3390/ijerph15122796 5. A. Hosny, C. Parmar, J. Quackenbush, L. Schwartz, H. Aerts, Artificial intelligence in radiology, Nat. Rev. Cancer, 18 (2018), 500–510. https://doi.org/10.1038/s41568-018-0016-5
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|