为可靠的人工智能医学提供数据特征。

Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhiyun Xue, Sameer K Antani
{"title":"为可靠的人工智能医学提供数据特征。","authors":"Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhiyun Xue, Sameer K Antani","doi":"10.1007/978-3-031-23599-3_1","DOIUrl":null,"url":null,"abstract":"<p><p>Research in Artificial Intelligence (AI)-based medical computer vision algorithms bear promises to improve disease screening, diagnosis, and subsequently patient care. However, these algorithms are highly impacted by the characteristics of the underlying data. In this work, we discuss various data characteristics, namely <i>Volume, Veracity, Validity, Variety</i>, and <i>Velocity,</i> that impact the design, reliability, and evolution of machine learning in medical computer vision. Further, we discuss each characteristic and the recent works conducted in our research lab that informed our understanding of the impact of these characteristics on the design of medical decision-making algorithms and outcome reliability.</p>","PeriodicalId":74648,"journal":{"name":"Recent trends in image processing and pattern recognition : 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 01-02, 2022, revised selected papers. International Conference on Recent Trends in Image Processing and...","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912175/pdf/nihms-1859534.pdf","citationCount":"0","resultStr":"{\"title\":\"Data Characterization for Reliable AI in Medicine.\",\"authors\":\"Sivaramakrishnan Rajaraman, Ghada Zamzmi, Feng Yang, Zhiyun Xue, Sameer K Antani\",\"doi\":\"10.1007/978-3-031-23599-3_1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Research in Artificial Intelligence (AI)-based medical computer vision algorithms bear promises to improve disease screening, diagnosis, and subsequently patient care. However, these algorithms are highly impacted by the characteristics of the underlying data. In this work, we discuss various data characteristics, namely <i>Volume, Veracity, Validity, Variety</i>, and <i>Velocity,</i> that impact the design, reliability, and evolution of machine learning in medical computer vision. Further, we discuss each characteristic and the recent works conducted in our research lab that informed our understanding of the impact of these characteristics on the design of medical decision-making algorithms and outcome reliability.</p>\",\"PeriodicalId\":74648,\"journal\":{\"name\":\"Recent trends in image processing and pattern recognition : 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 01-02, 2022, revised selected papers. International Conference on Recent Trends in Image Processing and...\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912175/pdf/nihms-1859534.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Recent trends in image processing and pattern recognition : 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 01-02, 2022, revised selected papers. International Conference on Recent Trends in Image Processing and...\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/978-3-031-23599-3_1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Recent trends in image processing and pattern recognition : 5th International Conference, RTIP2R 2022, Kingsville, TX, USA, December 01-02, 2022, revised selected papers. International Conference on Recent Trends in Image Processing and...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-031-23599-3_1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/11 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

基于人工智能(AI)的医学计算机视觉算法研究有望改善疾病筛查和诊断,进而改善病人护理。然而,这些算法深受基础数据特征的影响。在这项工作中,我们将讨论影响医学计算机视觉中机器学习的设计、可靠性和演进的各种数据特征,即数据量、真实性、有效性、多样性和速度。此外,我们还将讨论每个特征以及我们研究实验室最近开展的工作,这些工作有助于我们理解这些特征对医疗决策算法设计和结果可靠性的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Characterization for Reliable AI in Medicine.

Research in Artificial Intelligence (AI)-based medical computer vision algorithms bear promises to improve disease screening, diagnosis, and subsequently patient care. However, these algorithms are highly impacted by the characteristics of the underlying data. In this work, we discuss various data characteristics, namely Volume, Veracity, Validity, Variety, and Velocity, that impact the design, reliability, and evolution of machine learning in medical computer vision. Further, we discuss each characteristic and the recent works conducted in our research lab that informed our understanding of the impact of these characteristics on the design of medical decision-making algorithms and outcome reliability.

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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信