2003—2023年口腔癌智慧医疗文献循证可视化及对比分析

doi:10.7518/gjkq.2025026

摘要/Abstract

摘要：

目的运用文献计量学探究口腔癌智慧医疗领域的发展趋势、研究热点及未来方向，为后续研究提供参考。方法回顾性收集2003—2023年Web of Science Core Collection、Scopus和PubMed数据库口腔癌智慧医疗主题英文文献和中国知识基础设施工程（简称中国知网）数据库同主题中文文献，利用VOSviewer 1.6.18软件对纳入文献的国家、机构、作者、被引频次、关键词进行循证可视化对比分析。结果共纳入547篇英文文献和34篇中文文献，发文量均呈上升趋势，且近几年增长趋势更加明显；美国是该领域贡献最大的国家，与其他国家学术交流紧密，而我国跨国、跨机构、跨团队合作较局限，网络结构具有明显地域性。此外，人工智能辅助口腔癌诊治是国内外文献共同关注的重点，英文文献侧重新型诊断技术的深层探索，中文文献倾向智慧康养及中药网络药理学的应用探究。结论口腔癌智慧医疗的持续发展使其在人工智能辅助诊断、智慧康养和中药特色药理学方面的应用研究日益深远，早期预警筛查亟待成为智慧医疗关爱口腔健康的重要着力点。

关键词: 口腔癌, 智慧医疗, 循证可视化, 文献计量学, 对比分析

Abstract:

Objective This study aims to explore the development trends, research hotspots, and future directions of smart healthcare for oral cancer through bibliometrics, providing a reference for subsequent research. Methods English literature on smart healthcare for oral cancer in Web of Science Core Collection, Scopus, and PubMed databases and Chinese literature on the same topic in the CNKI database published in 2003-2023 were retrospectively collected. Meanwhile, the evidence-based visualization and comparative analysis of the countries, institutions, authors, citation frequency, and keywords included in the literature were performed with VOSviewer 1.6.18 software. Results A total of 547 English articles and 34 Chinese documents were included. An increasing trend in publication volume, especially in recent years, was observed. Among countries, the United States was the largest contributor to the field and had close academic exchanges with other countries, whereas cross-border, cross-institutional, and cross-team cooperation was limited in China. Moreover, network structure had regional characteri-stics. In addition, the artificial intelligence-assisted diagnosis and treatment of oral cancer are a common focus of attention in domestic and foreign literature. English literature focuses on the deep exploration of new diagnostic technologies, whereas Chinese literature tends to explore the application of intelligent health care and traditional Chinese medicine network pharmacology. Conclusion The conti-nuous development of smart healthcare for oral cancer has made the research on its application in artificial intelligence-assisted diagnosis, intelligent health care, and traditional Chinese medicine pharmacology increasingly profound. Early warning screening urgently needs to become an important focus of smart healthcare for oral health.

Key words: oral cancer, smart healthcare, evidence-based visualization, bibliometric, comparative analysis

中图分类号:

R782

廖永珍, 王晓辉, 邱洁, 周加靓, 丛丽. 2003—2023年口腔癌智慧医疗文献循证可视化及对比分析[J]. 国际口腔医学杂志, 2025, 52(1): 50-60.

Yongzhen Liao, Xiaohui Wang, Jie Qiu, Jialiang Zhou, Li Cong. Evidence-based visualization and comparative analysis of the literature on smart healthcare for oral cancer from 2003 to 2023[J]. Int J Stomatol, 2025, 52(1): 50-60.

图/表 7

图 1

图 2

图 3

图 4

表 1

被引频次排名前十的中英文文献"

文献	序号	标题	年份	被引频次
中文	1	APP软件在口腔癌游离皮瓣修复术后出院患者延续性护理中的应用	2018	18
	2	网络互动教育在口腔癌手术病人护理中的应用	2019	11
	3	数字化技术在口腔颌面部肿瘤精准外科诊疗中的应用	2020	11
	4	机器学习在颌面部囊肿及肿瘤中应用的研究进展	2020	9
	5	人工智能技术在口腔医学领域的应用进展	2020	8
	6	基于大规模临床数据深度学习的口腔疾病人工智能预防与诊断平台的构建	2020	8
	7	远程网络同行评价在口腔癌手术患者护理质量控制中的应用效果分析	2017	7
	8	口腔癌术后放疗患者智能精神状态及其影响因素研究	2015	6
	9	沉默生物钟基因PER1对口腔鳞状细胞癌细胞中生物钟基因网络的影响	2017	6
	10	口腔癌相关唾液肿瘤生物标志物的分析检测研究进展	2019	5
英文	1	Luminescent quantum clusters of gold in bulk by albumin-induced core etching of nanoparticles: metal ion sensing, metal-enhanced luminescence, and biolabeling	2010	225
	2	The terahertz electromagnetically induced transparency-like metamaterials for sensitive biosensors in the detection of cancer cells	2019	183
	3	Electrochemical sensor for multiplex biomarkers detection	2009	181
	4	Nano-bio-chips for high performance multiplexed protein detection: determinations of cancer biomarkers in serum and saliva using quantum dot bioconjugate labels	2009	178
	5	Ultrasensitive detection of cancer biomarkers in the clinic by use of a nanostructured microfluidic array	2012	155
	6	Deep learning-based survival prediction of oral cancer patients	2019	138
	7	Nanostructured zirconia decorated reduced graphene oxide based efficient biosensing platform for non-invasive oral cancer detection	2016	135
	8	Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning	2017	126
	9	Computer-assisted medical image classification for early diagnosis of oral cancer employing deep learning algorithm	2019	119
	10	YouTube as a source of information on mouth (oral) cancer	2016	111

表 1

图 5

图 6

参考文献 27

1	Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263.
2	Tarle M, Lukšić I. Pathogenesis and therapy of oral carcinogenesis[J]. Int J Mol Sci, 2024, 25(12): 6343.
3	Abati S, Bramati C, Bondi S, et al. Oral cancer and precancer: a narrative review on the relevance of early diagnosis[J]. Int J Environ Res Public Health, 2020, 17(24): 9160.
4	Nguyen DC, Pham QV, Pathirana PN, et al. Federa-ted learning for smart healthcare: a survey[J]. ACM Comput Surv, 2023, 55(3): 60.
5	Yang CH, Lee HL, Tsai WH, et al. Sustainable smart healthcare information portfolio strategy eva-luation: an integrated activity-based costing decision model[J]. Sustainability, 2020, 12(24): 10662.
6	张传洋, 郭宇, 庞宇飞, 等. 数智化医疗信息利用与服务模式框架构建[J]. 图书情报工作, 2023, 67(13): 49-58.
	Zhang CY, Guo Y, Pang YF, et al. Construction of medical information utilization and service framework for digital and intellectual transformation[J]. Libr Inf Serv, 2023, 67(13): 49-58.
7	杨善林, 范先群, 丁帅, 等. 医联网与智慧医疗健康管理[J]. 管理科学, 2021, 34(6): 71-75.
	Yang SL, Fan XQ, Ding S, et al. Internet of healthcare systems and smart medical health management[J]. J Manag Sci, 2021, 34(6): 71-75.
8	Kim JS, Kim BG, Hwang SH. Efficacy of artificial intelligence-assisted discrimination of oral cance-rous lesions from normal mucosa based on the oral mucosal image: a systematic review and meta-analysis[J]. Cancers, 2022, 14(14): 3499.
9	Wang TF, Huang RC, Yang SC, et al. Evaluating the effects of a mobile health App on reducing patient care needs and improving quality of life after oral cancer surgery: quasiexperimental study[J]. JMIR Mhealth Uhealth, 2020, 8(7): e18132.
10	季汉珍, 龚亚驰, 徐建如, 等. 构建 “平战结合” 式新型智慧传染病医院的研究与思考[J]. 中国医院管理, 2020, 40(11): 1-5.
	Ji HZ, Gong YC, Xu JR, et al. Study and thought on the construction of a new type of intelligent infectious disease hospitals in both peacetime and wartime[J]. Chin Hosp Manag, 2020, 40(11): 1-5.
11	van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping[J]. Scientometrics, 2010, 84(2): 523-538.
12	王权, 李杨, 杨珂璐, 等. 基于Web of Science和CNKI甲状腺癌文献循证可视化及对比分析[J]. 中国实用外科杂志, 2021, 41(6): 673-680, 690.
	Wang Q, Li Y, Yang KL, et al. Evidence-based vi-sualization and comparative analysis of literature on thyroid cancer based on Web of Science and CNKI[J]. Chin J Pract Surg, 2021, 41(6): 673-680, 690.
13	Al Dahdah M, Mishra RK. Digital health for all: the turn to digitized healthcare in India[J]. Soc Sci Med, 2023, 319: 114968.
14	Krishnan S. Digitalisation of Indian smart cities: post-covid-19 approaches to data, recognition and health monitoring[J]. Cambridge J Regions Econ Soc, 2023, 16(2): 349-359.
15	Miranda-Filho A, Bray F. Global patterns and trends in cancers of the lip, tongue and mouth[J]. Oral Oncol, 2020, 102: 104551.
16	Subash A, Bylapudi B, Thakur S, et al. Oral cancer in India, a growing problem: is limiting the exposure to avoidable risk factors the only way to reduce the disease burden[J]. Oral Oncol, 2022, 125: 105677.
17	Song BF, Zhang CC, Sunny S, et al. Interpretable and reliable oral cancer classifier with attention mechanism and expert knowledge embedding via attention map[J]. Cancers, 2023, 15(5): 1421.
18	Song BF, Sunny S, Li SB, et al. Mobile-based oral cancer classification for point-of-care screening[J]. J Biomed Opt, 2021, 26(6): 065003.
19	James BL, Sunny SP, Heidari AE, et al. Validation of a point-of-care optical coherence tomography device with machine learning algorithm for detection of oral potentially malignant and malignant lesions[J]. Cancers, 2021, 13(14): 3583.
20	梅春英, 王菡, 李晓军, 等. 智慧医疗的伦理和法律问题及其应对策略[J]. 中国医院管理, 2023, 43(3): 70-74.
	Mei CY, Wang H, Li XJ, et al. The ethical and legal problems of intelligent medicine and its countermeasures[J]. Chin Hosp Manag, 2023, 43(3): 70-74.
21	施敏, 邬庆超, 吴磊. 何以跨越智慧医疗数字鸿沟? 基于“敏捷治理”视角[J]. 卫生经济研究, 2023, 40(1): 61-64.
	Shi M, Wu QC, Wu L. How to bridge the digital divide in intelligent health care? From the perspective of agile governance[J]. Health Econ Res, 2023, 40(1): 61-64.
22	Xue XQ, Zeng YY, Zhang YJ, et al. A study on an application system for the sustainable development of smart healthcare in China[J]. IEEE Access, 2021, 9: 111960-111974.
23	林慧平, 徐婷, 林军. 人工智能在口腔癌和口腔潜在恶性疾病诊断中的研究进展[J]. 国际口腔医学杂志, 2023, 50(2): 138-145.
	Lin HP, Xu T, Lin J. Research progress on artificial intelligence techniques in diagnosis of oral cancer and potentially malignant disorders[J]. Int J Stomatol, 2023, 50(2): 138-145.
24	Dixit S, Kumar A, Srinivasan K. A current review of machine learning and deep learning models in oral cancer diagnosis: recent technologies, open challenges, and future research directions[J]. Diagnostics (Basel), 2023, 13(7): 1353.
25	Alhazmi A, Alhazmi Y, Makrami A, et al. Application of artificial intelligence and machine learning for prediction of oral cancer risk[J]. J Oral Pathol Med, 2021, 50(5): 444-450.
26	吴玮, 黄杰, 黄宇华, 等. 应用计算机辅助诊断技术对口腔鳞状细胞癌组织病理图像进行自动检测的价值[J]. 现代肿瘤医学, 2023, 31(3): 459-463.
	Wu W, Huang J, Huang YH, et al. The value of automatic detection of pathological images of oral squamous cell carcinoma by computer aided diagnosis[J]. J Mod Oncol, 2023, 31(3): 459-463.
27	Das N, Hussain E, Mahanta LB. Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network[J]. Neural Netw, 2020, 128: 47-60.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

[1]	曹梦颖,石蕊,于瀚雯,刘程程. 遥感成像技术在口腔疾病诊疗应用的研究进展[J]. 国际口腔医学杂志, 2025, 52(1): 107-116.
[2]	符天宇,张雪,王思琪,郭程祎,董晓宇,程亚鹏,李锐. 碳点在口腔颌面部恶性肿瘤的诊断及治疗中的应用[J]. 国际口腔医学杂志, 2025, 52(1): 25-33.
[3]	吴媚, 梁妍景, 彭雪沛, 陈卫宏, 郭星铜, 侯黎莉. 口腔癌术后言语功能影响因素分析[J]. 国际口腔医学杂志, 2025, 52(1): 42-49.
[4]	傅豫, 何薇, 黄兰. 铁死亡在口腔疾病中的研究进展[J]. 国际口腔医学杂志, 2024, 51(1): 36-44.
[5]	姜玥莹,何宇添,李婷,周蓉卉. 近红外荧光探针在口腔癌诊断中应用的研究进展[J]. 国际口腔医学杂志, 2023, 50(4): 407-413.
[6]	范琳,孙江. 微针在口腔医学中的应用[J]. 国际口腔医学杂志, 2023, 50(4): 472-478.
[7]	林慧平,徐婷,林军. 人工智能在口腔癌和口腔潜在恶性疾病诊断中的研究进展[J]. 国际口腔医学杂志, 2023, 50(2): 138-145.
[8]	王太萍,石兴莲,李喆臻,刘梅,姜健红. 口腔癌患者心理因素及干预现状分析[J]. 国际口腔医学杂志, 2023, 50(2): 203-209.
[9]	吕欣,樊永杰. 无托槽隐形矫治技术研究热点的可视化分析[J]. 国际口腔医学杂志, 2023, 50(1): 72-81.
[10]	陈荟宇,白明茹,叶玲. 信号素3A与口腔常见病关系的研究进展[J]. 国际口腔医学杂志, 2022, 49(5): 593-599.
[11]	田而慷,向倩蓉,赵欣然,彭佳涵,舒睿. 口腔诊疗中人工智能的运用[J]. 国际口腔医学杂志, 2021, 48(4): 475-484.
[12]	黄璐,戴杰,吴燕岷. 唾液生物标志物在口腔癌筛查中的应用[J]. 国际口腔医学杂志, 2020, 47(1): 68-75.
[13]	原振英,管翠强,南欣荣. DNA甲基化与口腔疾病的研究进展[J]. 国际口腔医学杂志, 2019, 46(4): 437-441.
[14]	李倩,张平,陈娇,曾昕,冯云. 唾液组学在口腔癌诊断中的应用[J]. 国际口腔医学杂志, 2018, 45(6): 710-715.
[15]	韩曈曈,陈乔尔,朱友明. p53相关长链非编码RNA及其与口腔癌的关系[J]. 国际口腔医学杂志, 2018, 45(5): 597-602.