严重哮喘的大数据研究。

IF 2.5 Q2 RESPIRATORY SYSTEM Tuberculosis and Respiratory Diseases Pub Date : 2024-07-01 Epub Date: 2024-03-05 DOI:10.4046/trd.2023.0186
Sang Hyuk Kim, Youlim Kim
{"title":"严重哮喘的大数据研究。","authors":"Sang Hyuk Kim, Youlim Kim","doi":"10.4046/trd.2023.0186","DOIUrl":null,"url":null,"abstract":"<p><p>The continuously increasing prevalence of severe asthma has imposed an increasing burden worldwide. Despite the emergence of novel therapeutic agents, management of severe asthma remains challenging. Insights garnered from big data may be helpful in the effort to determine the complex nature of severe asthma. In the field of asthma research, a vast amount of big data from various sources, including electronic health records, national claims data, and international cohorts, is now available. However, understanding of the strengths and limitations is required for proper utilization of specific datasets. Use of big data, along with advancements in artificial intelligence techniques, could potentially facilitate the practice of precision medicine in management of severe asthma.</p>","PeriodicalId":23368,"journal":{"name":"Tuberculosis and Respiratory Diseases","volume":" ","pages":"213-220"},"PeriodicalIF":2.5000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222096/pdf/","citationCount":"0","resultStr":"{\"title\":\"Big Data Research on Severe Asthma.\",\"authors\":\"Sang Hyuk Kim, Youlim Kim\",\"doi\":\"10.4046/trd.2023.0186\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The continuously increasing prevalence of severe asthma has imposed an increasing burden worldwide. Despite the emergence of novel therapeutic agents, management of severe asthma remains challenging. Insights garnered from big data may be helpful in the effort to determine the complex nature of severe asthma. In the field of asthma research, a vast amount of big data from various sources, including electronic health records, national claims data, and international cohorts, is now available. However, understanding of the strengths and limitations is required for proper utilization of specific datasets. Use of big data, along with advancements in artificial intelligence techniques, could potentially facilitate the practice of precision medicine in management of severe asthma.</p>\",\"PeriodicalId\":23368,\"journal\":{\"name\":\"Tuberculosis and Respiratory Diseases\",\"volume\":\" \",\"pages\":\"213-220\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222096/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tuberculosis and Respiratory Diseases\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4046/trd.2023.0186\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/3/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"RESPIRATORY SYSTEM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tuberculosis and Respiratory Diseases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4046/trd.2023.0186","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/3/5 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"RESPIRATORY SYSTEM","Score":null,"Total":0}
引用次数: 0

摘要

重症哮喘发病率的持续上升给全世界带来了日益沉重的负担。尽管出现了新型治疗药物,但重症哮喘的治疗仍然充满挑战。从大数据中获得的洞察力可能有助于确定重症哮喘的复杂性。在哮喘研究领域,目前已有大量来自不同来源的大数据,包括电子健康记录、国家索赔数据和国际队列。然而,要正确利用特定数据集,就必须了解其优势和局限性。大数据的使用以及人工智能技术的进步有可能促进在重症哮喘管理中实施精准医疗。
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
Big Data Research on Severe Asthma.

The continuously increasing prevalence of severe asthma has imposed an increasing burden worldwide. Despite the emergence of novel therapeutic agents, management of severe asthma remains challenging. Insights garnered from big data may be helpful in the effort to determine the complex nature of severe asthma. In the field of asthma research, a vast amount of big data from various sources, including electronic health records, national claims data, and international cohorts, is now available. However, understanding of the strengths and limitations is required for proper utilization of specific datasets. Use of big data, along with advancements in artificial intelligence techniques, could potentially facilitate the practice of precision medicine in management of severe asthma.

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
CiteScore
5.30
自引率
0.00%
发文量
42
审稿时长
12 weeks
期刊最新文献
Bibliometric Analysis of Nontuberculous Mycobacteria Research in South Korea. Increased neutrophil elastase in affected lobes of bronchiectasis and correlation of its levels between sputum and bronchial lavage fluid. Korean Guidelines for Diagnosis and Management of Interstitial Lung Diseases: Connective Tissue Disease Associated Interstitial Lung Disease. Understanding of patients with severe COVID-19 using lung ultrasound. Disease Severity and Activity in Bronchiectasis: A Paradigm Shift in Bronchiectasis Management.
×
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