从2015年到2023年,对深度学习在癌症中的应用进行了图书统计分析
Ruiyu Wang1,2, Shu Huang3,4, Ping Wang1,2
1Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Street Taiping No.25, Region Jiangyang, Luzhou, Sichuan Province, 646099, China.
概括
深度学习 (DL) 在癌症研究中的应用正在迅速增加. 本文库分析探讨了研究趋势,确定了癌症预测和诊断等关键领域,并强调了未来与基因组学的整合.
科学领域:
- 图书统计学 图书统计学
- 人工智能的人工智能
- 在瘤学瘤学.
背景情况:
- 深度学习 (DL) 在各个领域取得了重大进展,特别是癌症研究.
- 在瘤学中对DL应用的文献分析存在差距.
- 这项研究解决了了解DL在癌症中的研究格局的需要.
研究的目的:
- 在癌症研究中对DL应用进行文献计量分析.
- 确定当前的研究状况和新兴热点.
- 提供对全球研究成果和趋势的见解.
主要方法:
- 数据来源于科学网络核心集合数据库.
- 使用Biblioshiny,VOSviewer和CiteSpace进行的图书识别分析.
- 分析包括出版物量,引用,国家,机构,作者,期刊,参考文献和关键词.
主要成果:
- 确定了6016篇原创文章,出版物和引用的总体上升趋势.
- 中国在出版物方面领先,美国在引用方面领先,沙特阿拉伯在中心地位方面领先.
- 关键的研究领域包括预测,检测,分类和诊断乳腺癌,肺癌和皮肤癌.
结论:
- 癌症中DL的研究量正在稳步增长.
- 未来的趋势可能涉及扩大DL应用,提高准确性,并与蛋白质预测和基因组学集成.
- 持续的研究对于推进DL在瘤学中的作用至关重要.
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