Zhongguo quanke yixue (Feb 2024)
Research Trends in Artificial Intelligence in Gastric Cancer Diagnosis and Treatment: a 20-year Bibliometric Analysis
Abstract
Background The number of researches on the application of artificial intelligence (AI) to diagnosis and treatment of gastric cancer has been increasing in recent years, but no researcher has systematically analyzed it using bibliometric analysis. Objective To analyze the researches on the application of AI to diagnosis and treatment of gastric cancer, explore the research hotspots and development trends from 2003 to 2022. Methods On November 06, 2022, Web of Science (WOS) core collection database was searched by computer to obtain studies on the application of AI to gastric cancer diagnosis and treatment, and VOSviewer 1.6.18 software was used to visualize and analyze inter-country (region), inter-institution, and inter-author collaborations, co-cited authors, keyword co-occurrences and overlays through bibliometric analysis. CiteSpace 5.7.R5 software was used to perform institutional betweenness centrality analysis, journal biplot overlay, cluster analysis of co-cited literature for the last 6 years, co-cited literature clustering timeline graph analysis and reference bursting analysis. Excel 2019 software was used to plot bar graphs of the volume of publications and descriptive analysis tables of countries (regions), institutions, journals, authors, cited references and keywords. Results A total of 703 papers were included, and the annual publication volume of the application of AI to gastric cancer diagnosis and treatment showed an overall increasing trend from 2003-2022, with a rapid increase after 2017 and the most rapid growth from 2019-2021. The top publishing country, institution and author was China, Chinese Academy of Sciences and TADA TOMOHIRO, respectively. The top three co-cited authors of BRAY FREDDIE, HIRASAWA TOSHIAKI and JIANG YUMING had made significant contributions to the field. Frontiers in Oncology was the journal with the highest publication volume, and Gastrointestinal Endoscopy was the most influential journal among the top ten journals for researches related to the application of AI to the diagnosis and treatment of gastric cancer. The citing journals mainly focused on the two fields of "Medicine, Medical, Clinical" and "Molecular, Biology, Immunology". And the cited journals mainly focused on the two fields of "Molecular, Biology, Genetics" and "Health, Nursing, Medicine". The top-ranked literature in terms of total citations titled Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. All keywords were classified into 4 categories based on keyword clustering results, including AI-assisted biological research of gastric cancer, AI-assisted endoscopic diagnosis of gastric cancer, AI-assisted pathological diagnosis of gastric cancer, and AI-assisted non-endoscopic treatment and prognosis prediction of gastric cancer. Deep learning, convolutional neural network, imaging histology, gastrointestinal endoscopy, pathology and immunotherapy were the current research hotspots. Conclusion AI has a broad application prospect in gastric cancer diagnosis and treatment, and more and more scholars are devoted to AI in gastric cancer diagnosis and treatment. Currently, AI has been widely studied in the biology, diagnosis, staging, efficacy assessment and prognosis prediction of gastric cancer. The results of this study can provide a reference for scholars engaged in research work related to AI and gastric cancer.
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