The Unreasonable Effectiveness, and Difficulty, of Data in Healthcare

Peter Lee
{"title":"The Unreasonable Effectiveness, and Difficulty, of Data in Healthcare","authors":"Peter Lee","doi":"10.1145/3292500.3330645","DOIUrl":null,"url":null,"abstract":"Data and data analysis are widely assumed to be the key part of the solution to healthcare systems' problems. Indeed, there are countless ways in which data can be converted into better medical diagnostic tools, more effective therapeutics, and improved productivity for clinicians. But while there is clearly great potential, some big challenges remain to make this all a reality, including making access to health data easier, addressing privacy and ethics concerns, and ensuring the clinical safety of \"learning\" systems. This talk illustrates what is possible in healthcare technology, and details key challenges that currently prevent this from becoming a reality.","PeriodicalId":186134,"journal":{"name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3292500.3330645","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Data and data analysis are widely assumed to be the key part of the solution to healthcare systems' problems. Indeed, there are countless ways in which data can be converted into better medical diagnostic tools, more effective therapeutics, and improved productivity for clinicians. But while there is clearly great potential, some big challenges remain to make this all a reality, including making access to health data easier, addressing privacy and ethics concerns, and ensuring the clinical safety of "learning" systems. This talk illustrates what is possible in healthcare technology, and details key challenges that currently prevent this from becoming a reality.
医疗保健中数据的不合理有效性和难度
数据和数据分析被广泛认为是解决医疗保健系统问题的关键部分。事实上,有无数种方法可以将数据转化为更好的医疗诊断工具、更有效的治疗方法,并提高临床医生的工作效率。但是,尽管有明显的巨大潜力,但要使这一切成为现实,仍然存在一些重大挑战,包括使获取健康数据更容易,解决隐私和伦理问题,以及确保“学习”系统的临床安全。本次演讲阐述了医疗保健技术的可能性,并详细介绍了目前阻碍其成为现实的关键挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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