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癌症纳米技术的全球趋势:一种基于内容和文献计量特征的定性科学图谱,用于机器学习文本分类

Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification.

作者信息

Millagaha Gedara Nuwan Indika, Xu Xuan, DeLong Robert, Aryal Santosh, Jaberi-Douraki Majid

机构信息

1DATA Consortium, Kansas State University Olathe, Olathe, KS 66061, USA.

Department of Mathematics, K-State, 22201 W Innovation Dr. Olathe, Olathe, KS 66061, USA.

出版信息

Cancers (Basel). 2021 Sep 1;13(17):4417. doi: 10.3390/cancers13174417.

DOI:10.3390/cancers13174417
PMID:34503227
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8431703/
Abstract

This study presents a new way to investigate comprehensive trends in cancer nanotechnology research in different countries, institutions, and journals providing critical insights to prevention, diagnosis, and therapy. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000-2021. Inspired by hybrid medical models and content-based and bibliometric features for machine learning models, our results show cancer nanotechnology studies have expanded exponentially since 2010. The highest production of articles in cancer nanotechnology is mainly from US institutions, with several countries, notably the USA, China, the UK, India, and Iran as concentrated focal points as centers of cancer nanotechnology research, especially in the last five years. The analysis shows the greatest overlap between nanotechnology and DNA, RNA, iron oxide or mesoporous silica, breast cancer, and cancer diagnosis and cancer treatment. Moreover, more than 50% of the information related to the keywords, authors, institutions, journals, and countries are considerably investigated in the form of publications from the top 100 journals. This study has the potential to provide past and current lines of research that can unmask comprehensive trends in cancer nanotechnology, key research topics, or the most productive countries and authors in the field.

摘要

本研究提出了一种新方法,用于调查不同国家、机构和期刊中癌症纳米技术研究的综合趋势,为癌症预防、诊断和治疗提供关键见解。本文在2000年至2021年期间,利用PubMed数据库对癌症纳米技术应用了文献计量分析的定性方法。受混合医学模型以及机器学习模型基于内容和文献计量特征的启发,我们的研究结果表明,自2010年以来,癌症纳米技术研究呈指数级增长。癌症纳米技术领域文章产量最高的主要来自美国机构,有几个国家,特别是美国、中国、英国、印度和伊朗,作为癌症纳米技术研究的集中焦点,尤其是在过去五年。分析表明,纳米技术与DNA、RNA、氧化铁或介孔二氧化硅、乳腺癌以及癌症诊断和癌症治疗之间的重叠度最高。此外,与关键词、作者、机构、期刊和国家相关的信息中,超过50%是以排名前100的期刊发表的形式进行了大量研究。本研究有潜力提供过去和当前的研究方向,揭示癌症纳米技术的综合趋势、关键研究课题,或该领域最具生产力的国家和作者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/38d05574c71f/cancers-13-04417-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/5bbeaf7746ea/cancers-13-04417-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/fdc33759fd61/cancers-13-04417-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/dab024b6ea4f/cancers-13-04417-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/56343e7b34da/cancers-13-04417-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/0a78ecbd7df0/cancers-13-04417-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/80ab400c23a9/cancers-13-04417-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/e15ff2aa5bb3/cancers-13-04417-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/480a53ef9f2f/cancers-13-04417-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/7c22469c30e9/cancers-13-04417-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/a05f293e2a68/cancers-13-04417-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/38d05574c71f/cancers-13-04417-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/5bbeaf7746ea/cancers-13-04417-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/fdc33759fd61/cancers-13-04417-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/dab024b6ea4f/cancers-13-04417-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/56343e7b34da/cancers-13-04417-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/0a78ecbd7df0/cancers-13-04417-g005a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/80ab400c23a9/cancers-13-04417-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/e15ff2aa5bb3/cancers-13-04417-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/480a53ef9f2f/cancers-13-04417-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/7c22469c30e9/cancers-13-04417-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/a05f293e2a68/cancers-13-04417-g010a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/da53/8431703/38d05574c71f/cancers-13-04417-g011.jpg

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本文引用的文献

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2
Pulmonary adverse drug event data in hypertension with implications on COVID-19 morbidity.高血压药物不良反应与 COVID-19 发病率相关的肺部数据。
Sci Rep. 2021 Jun 25;11(1):13349. doi: 10.1038/s41598-021-92734-7.
3
A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research.
一种用于整理比较药代动力学数据的自动化可定制实时网络爬虫:基于研究的综合文章库的智能汇编。
Pharmaceutics. 2023 Apr 30;15(5):1384. doi: 10.3390/pharmaceutics15051384.
4
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Front Oncol. 2023 Jan 27;13:1111985. doi: 10.3389/fonc.2023.1111985. eCollection 2023.
5
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6
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7
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ACS Pharmacol Transl Sci. 2022 Jun 22;5(7):449-457. doi: 10.1021/acsptsci.2c00041. eCollection 2022 Jul 8.
一个带有完整注释的犬类乳腺癌全切片图像数据集,以辅助人类乳腺癌研究。
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