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| 我国关于胃癌预测模型研究热点及展望——基于信息可视化工具研究 |
| 作者：韩文政1 高华敏2 梁思3 |
| 单位：1. 河北大学附属医院 麻醉科, 河北 保定 071002; 2. 河北大学 管理学院, 河北 保定 071002; 3. 河北大学 附属医院, 河北 保定 071002 |
| 关键词：胃癌 预测模型 发展态势 CiteSpace 可视化分析 |
| 分类号：R735.2 |
| 出版年·卷·期（页码）：2025·44·第一期（113-120） |
| 摘要： |
目的:分析国内关于胃癌预测模型的研究现状,为未来国内胃癌术后并发症预测模型的研究提供参考和方向。方法:应用CiteSpace知识图谱可视化工具,基于中国知网2016年1月1日至2024年7月3日对胃癌预测模型的研究文献为研究对象,统计年发文量,绘制作者合作网络图谱,并根据关键词共线、聚类、时序、突现图谱对术后并发症研究模型主题下的研究热点进行分析,探究该主题研究的演进过程,分析发展趋势及意义。结果:共获得314篇有关胃癌预测模型的文献,277篇有效文献。刘洋、丁平安、杜耀、李勇、任莹坤、秦艳茹、王泽正、常紫薇等为胃癌预测模型领域的核心作者,但合作网络松散,作者之间的合作密度较低。研究样本机构共有155个,其中发文量最多的机构是兰州大学,发文量为10篇。我国胃癌预测模型研究文献中关键词的聚类标签分别为生物信息学、淋巴结转移、危险因素、体层摄影术、风险预测模型、预后、影像组学、受益人群、遗传风险、免疫治疗、恶性腹水等。近年来研究者对胃癌预测模型的研究,不仅在研究方向上进行了创新,在构建模型、验证模型的方法上也有了很大的尝试和改进,并得到了不少可观的成果。结论:通过使用CiteSpace绘制的图谱及表格分析得出,胃癌预测模型的研究在未来将会成为热门研究方向。以不同预测方向、不同构建模型方法为基点构建精细化的胃癌预测模型或将成为研究热点,研究者应基于多种机器学习方法进行多中心、大样本、质量高的前瞻性研究,并将构建的预测模型尝试应用于临床实践以构建高性能、高可靠、个体化的胃癌预测模型。 |
Objective: To analyze the current research status of gastric cancer prediction models in China that can provide reference and direction for the future study of models predicting postoperative complications in China. Methods: In this study, CiteSpace knowledge atlas visualization tool was used to estimate the annual 2024 of articles on the model of predicting gastric cancer based on the research literature of CNKI from January 1,2016 to July 3,2016, as well as to draw the authors' cooperative network Atlas, and to analyze the hot topics under the theme of postoperative complications research model according to the keyword collinearity, clustering, time series, and emergent atlas, and to explore the evolution process of this theme research, analyze the development trend and significance. Results: A total of 314 articles on gastric cancer and prediction models were obtained, of which 277 were valid.Liu Yang, DING Ping An, DU Yao, LI Yong, REN Yingkun, QIN Yanru, WANG Zezheng, and CHANG Ziwei were the core authors in the field of gastric cancer prediction models. However, they did not cooperate much. There were 155 institutions researching sample, of which Lanzhou University published 10, the largest number of articles. The keyword cluster tags in the Chinese gastric cancer prediction model research literature were bioinformatics, lymph node metastasis, risk factors, tomography, risk prediction model, prognosis, radiomics, beneficiary population, genetic risk, immunotherapy, malignant ascites, etc. In recent years, researchers had not only innovated in the research direction, but also made great attempts and improvements in the methods of model construction and model validation, and had obtained considerable results. Conclusion: Through the analysis of Atlas and tables drawn by CiteSpace, the prediction model of gastric cancer will become a hot research direction in the future, which will become a research hotspot to construct a refined prediction model of gastric cancer based on different prediction directions and methods, researchers should conduct a multi-center, large-sample, high-quality prospective study based on multiple machine learning methods, the prediction model was applied to clinical practice to construct a high-performance, high-reliability, individualized prediction model of gastric cancer. |
| 参考文献： |
[1] SMYTH E C, NILSSON M, GRABSCH H I, et al.Gastric cancer[J]. Lancet, 2020, 396(10251):635-648. |
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