利用BERTopic方法对骨再生的新趋势进行建模。

IF 2.4 4区 医学 Q4 CELL & TISSUE ENGINEERING Regenerative medicine Pub Date : 2023-09-01 DOI:10.2217/rme-2023-0096
Stefano Guizzardi, Maria Teresa Colangelo, Prisco Mirandola, Carlo Galli
{"title":"利用BERTopic方法对骨再生的新趋势进行建模。","authors":"Stefano Guizzardi,&nbsp;Maria Teresa Colangelo,&nbsp;Prisco Mirandola,&nbsp;Carlo Galli","doi":"10.2217/rme-2023-0096","DOIUrl":null,"url":null,"abstract":"<p><p><b>Aim:</b> Bibliometric surveys are time-consuming endeavors, which cannot be scaled up to meet the challenges of ever-expanding fields, such as bone regeneration. Artificial intelligence, however, can provide smart tools to screen massive amounts of literature, and we relied on this technology to automatically identify research topics. <b>Materials & methods:</b> We used the BERTopic algorithm to detect the topics in a corpus of MEDLINE manuscripts, mapping their similarities and highlighting research hotspots. <b>Results:</b> Using BERTopic, we identified 372 topics and were able to assess the growing importance of innovative and recent fields of investigation such as 3D printing and extracellular vescicles. <b>Conclusion:</b> BERTopic appears as a suitable tool to set up automatic screening routines to track the progress in bone regeneration.</p>","PeriodicalId":21043,"journal":{"name":"Regenerative medicine","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling new trends in bone regeneration, using the BERTopic approach.\",\"authors\":\"Stefano Guizzardi,&nbsp;Maria Teresa Colangelo,&nbsp;Prisco Mirandola,&nbsp;Carlo Galli\",\"doi\":\"10.2217/rme-2023-0096\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b>Aim:</b> Bibliometric surveys are time-consuming endeavors, which cannot be scaled up to meet the challenges of ever-expanding fields, such as bone regeneration. Artificial intelligence, however, can provide smart tools to screen massive amounts of literature, and we relied on this technology to automatically identify research topics. <b>Materials & methods:</b> We used the BERTopic algorithm to detect the topics in a corpus of MEDLINE manuscripts, mapping their similarities and highlighting research hotspots. <b>Results:</b> Using BERTopic, we identified 372 topics and were able to assess the growing importance of innovative and recent fields of investigation such as 3D printing and extracellular vescicles. <b>Conclusion:</b> BERTopic appears as a suitable tool to set up automatic screening routines to track the progress in bone regeneration.</p>\",\"PeriodicalId\":21043,\"journal\":{\"name\":\"Regenerative medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Regenerative medicine\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.2217/rme-2023-0096\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CELL & TISSUE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regenerative medicine","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.2217/rme-2023-0096","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CELL & TISSUE ENGINEERING","Score":null,"Total":0}
引用次数: 0

摘要

目的:文献计量学调查是一项耗时的工作,它不能扩大规模以满足不断扩大的领域的挑战,例如骨再生。然而,人工智能可以提供智能工具来筛选大量文献,我们依靠这项技术来自动识别研究主题。材料与方法:我们使用BERTopic算法检测MEDLINE手稿语料库中的主题,绘制其相似度并突出研究热点。结果:使用BERTopic,我们确定了372个主题,并能够评估创新和最新研究领域(如3D打印和细胞外囊泡)日益增长的重要性。结论:BERTopic是建立自动筛选程序以跟踪骨再生进展的合适工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Modeling new trends in bone regeneration, using the BERTopic approach.

Aim: Bibliometric surveys are time-consuming endeavors, which cannot be scaled up to meet the challenges of ever-expanding fields, such as bone regeneration. Artificial intelligence, however, can provide smart tools to screen massive amounts of literature, and we relied on this technology to automatically identify research topics. Materials & methods: We used the BERTopic algorithm to detect the topics in a corpus of MEDLINE manuscripts, mapping their similarities and highlighting research hotspots. Results: Using BERTopic, we identified 372 topics and were able to assess the growing importance of innovative and recent fields of investigation such as 3D printing and extracellular vescicles. Conclusion: BERTopic appears as a suitable tool to set up automatic screening routines to track the progress in bone regeneration.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Regenerative medicine
Regenerative medicine 医学-工程:生物医学
CiteScore
4.20
自引率
3.70%
发文量
82
审稿时长
6-12 weeks
期刊介绍: Regenerative medicine replaces or regenerates human cells, tissue or organs, to restore or establish normal function*. Since 2006, Regenerative Medicine has been at the forefront of publishing the very best papers and reviews covering the entire regenerative medicine sector. The journal focusses on the entire spectrum of approaches to regenerative medicine, including small molecule drugs, biologics, biomaterials and tissue engineering, and cell and gene therapies – it’s all about regeneration and not a specific platform technology. The journal’s scope encompasses all aspects of the sector ranging from discovery research, through to clinical development, through to commercialization. Regenerative Medicine uniquely supports this important area of biomedical science and healthcare by providing a peer-reviewed journal totally committed to publishing the very best regenerative medicine research, clinical translation and commercialization. Regenerative Medicine provides a specialist forum to address the important challenges and advances in regenerative medicine, delivering this essential information in concise, clear and attractive article formats – vital to a rapidly growing, multidisciplinary and increasingly time-constrained community. Despite substantial developments in our knowledge and understanding of regeneration, the field is still in its infancy. However, progress is accelerating. The next few decades will see the discovery and development of transformative therapies for patients, and in some cases, even cures. Regenerative Medicine will continue to provide a critical overview of these advances as they progress, undergo clinical trials, and eventually become mainstream medicine.
期刊最新文献
Industry updates from the field of stem cell research and regenerative medicine in August 2024. Ultrasound-guided injection using leucocyte-rich platelet-rich plasma for treatment of meniscal injuries in a duathlete: a case report. Influencing factors and repair advancements in rodent models of peripheral nerve regeneration. Extracellular vesicles for corneal regeneration: the new frontier. Industry updates from the field of stem cell research and regenerative medicine in July 2024.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1