人工智能增强的基于分子的精准肿瘤临床决策。

IF 3.4 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Emerging Topics in Life Sciences Pub Date : 2021-12-21 DOI:10.1042/ETLS20210220
Jia Zeng, Md Abu Shufean
{"title":"人工智能增强的基于分子的精准肿瘤临床决策。","authors":"Jia Zeng,&nbsp;Md Abu Shufean","doi":"10.1042/ETLS20210220","DOIUrl":null,"url":null,"abstract":"<p><p>The rapid growth and decreasing cost of Next-generation sequencing (NGS) technologies have made it possible to conduct routine large panel genomic sequencing in many disease settings, especially in the oncology domain. Furthermore, it is now known that optimal disease management of patients depends on individualized cancer treatment guided by comprehensive molecular testing. However, translating results from molecular sequencing reports into actionable clinical insights remains a challenge to most clinicians. In this review, we discuss about some representative systems that leverage artificial intelligence (AI) to facilitate some processes of clinicians' decision making based upon molecular data, focusing on their application in precision oncology. Some limitations and pitfalls of the current application of AI in clinical decision making are also discussed.</p>","PeriodicalId":46394,"journal":{"name":"Emerging Topics in Life Sciences","volume":"5 6","pages":"757-764"},"PeriodicalIF":3.4000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/f4/ad/ETLS-5-757.PMC8786281.pdf","citationCount":"4","resultStr":"{\"title\":\"Molecular-based precision oncology clinical decision making augmented by artificial intelligence.\",\"authors\":\"Jia Zeng,&nbsp;Md Abu Shufean\",\"doi\":\"10.1042/ETLS20210220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The rapid growth and decreasing cost of Next-generation sequencing (NGS) technologies have made it possible to conduct routine large panel genomic sequencing in many disease settings, especially in the oncology domain. Furthermore, it is now known that optimal disease management of patients depends on individualized cancer treatment guided by comprehensive molecular testing. However, translating results from molecular sequencing reports into actionable clinical insights remains a challenge to most clinicians. In this review, we discuss about some representative systems that leverage artificial intelligence (AI) to facilitate some processes of clinicians' decision making based upon molecular data, focusing on their application in precision oncology. Some limitations and pitfalls of the current application of AI in clinical decision making are also discussed.</p>\",\"PeriodicalId\":46394,\"journal\":{\"name\":\"Emerging Topics in Life Sciences\",\"volume\":\"5 6\",\"pages\":\"757-764\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2021-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/f4/ad/ETLS-5-757.PMC8786281.pdf\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Emerging Topics in Life Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1042/ETLS20210220\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Emerging Topics in Life Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1042/ETLS20210220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 4

摘要

新一代测序(NGS)技术的快速发展和成本的降低使得在许多疾病环境中进行常规的大面板基因组测序成为可能,特别是在肿瘤学领域。此外,目前已知患者的最佳疾病管理取决于以综合分子检测为指导的个体化癌症治疗。然而,将分子测序报告的结果转化为可操作的临床见解对大多数临床医生来说仍然是一个挑战。在这篇综述中,我们讨论了一些有代表性的系统,利用人工智能(AI)来促进临床医生基于分子数据的决策过程,重点介绍了它们在精确肿瘤学中的应用。本文还讨论了目前人工智能在临床决策中应用的一些局限性和缺陷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

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
Molecular-based precision oncology clinical decision making augmented by artificial intelligence.

The rapid growth and decreasing cost of Next-generation sequencing (NGS) technologies have made it possible to conduct routine large panel genomic sequencing in many disease settings, especially in the oncology domain. Furthermore, it is now known that optimal disease management of patients depends on individualized cancer treatment guided by comprehensive molecular testing. However, translating results from molecular sequencing reports into actionable clinical insights remains a challenge to most clinicians. In this review, we discuss about some representative systems that leverage artificial intelligence (AI) to facilitate some processes of clinicians' decision making based upon molecular data, focusing on their application in precision oncology. Some limitations and pitfalls of the current application of AI in clinical decision making are also discussed.

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
7.70
自引率
0.00%
发文量
94
期刊最新文献
Bacterial acetate metabolism and its influence on human epithelia. Dinner date: Neisseria gonorrhoeae central carbon metabolism and pathogenesis. The nitric oxide paradox: antimicrobial and inhibitor of antibiotic efficacy. Copper management strategies in obligate bacterial symbionts: balancing cost and benefit. Metalloproteome plasticity - a factor in bacterial pathogen adaptive responses?
×
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