以人为本的可解释人工智能在电子健康的边缘

Joydeb Dutta, Deepak Puthal
{"title":"以人为本的可解释人工智能在电子健康的边缘","authors":"Joydeb Dutta, Deepak Puthal","doi":"10.1109/EDGE60047.2023.00044","DOIUrl":null,"url":null,"abstract":"Explainable Artificial Intelligence (XAI) is a new paradigm of Artificial Intelligence (AI) that is giving different AI/ Machine Learning (ML) models a boost to penetrate sectors where people are thinking about adopting AI. This work focuses on the adoption of XAI in the health sector. It portrays that careful integration of XAI in both cloud and edge could change the whole healthcare industry and make humans more aware of their present health conditions, which is the need of the hour. To demonstrate the same, we have done an experiment based on the prediction of a particular medical condition called \"cardiac arrest\" in a specific subject group (patients who are 70 years old). Here, based on the explanation provided by the XAI model (e.g., SHAP, LIME) at Cloud and Edge, our system can predict the chances of a \"cardiac arrest\" for the subject with a valid explanation. This type of model will be the next big upgrade in the healthcare industry in terms of automation and a self-explanatory system that works as a personal health assistant for individuals.","PeriodicalId":369407,"journal":{"name":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Human-Centered Explainable AI at the Edge for eHealth\",\"authors\":\"Joydeb Dutta, Deepak Puthal\",\"doi\":\"10.1109/EDGE60047.2023.00044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Explainable Artificial Intelligence (XAI) is a new paradigm of Artificial Intelligence (AI) that is giving different AI/ Machine Learning (ML) models a boost to penetrate sectors where people are thinking about adopting AI. This work focuses on the adoption of XAI in the health sector. It portrays that careful integration of XAI in both cloud and edge could change the whole healthcare industry and make humans more aware of their present health conditions, which is the need of the hour. To demonstrate the same, we have done an experiment based on the prediction of a particular medical condition called \\\"cardiac arrest\\\" in a specific subject group (patients who are 70 years old). Here, based on the explanation provided by the XAI model (e.g., SHAP, LIME) at Cloud and Edge, our system can predict the chances of a \\\"cardiac arrest\\\" for the subject with a valid explanation. This type of model will be the next big upgrade in the healthcare industry in terms of automation and a self-explanatory system that works as a personal health assistant for individuals.\",\"PeriodicalId\":369407,\"journal\":{\"name\":\"2023 IEEE International Conference on Edge Computing and Communications (EDGE)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Edge Computing and Communications (EDGE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDGE60047.2023.00044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Edge Computing and Communications (EDGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDGE60047.2023.00044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

可解释人工智能(XAI)是人工智能(AI)的一种新范式,它推动了不同的人工智能/机器学习(ML)模型进入人们正在考虑采用人工智能的领域。这项工作的重点是在卫生部门采用人工智能。它描绘了XAI在云和边缘的精心集成可以改变整个医疗保健行业,并使人类更加了解自己目前的健康状况,这是时代的需要。为了证明这一点,我们在一组特定的受试者(70岁以上的患者)中进行了一项实验,该实验基于一种被称为“心脏骤停”的特殊医学状况的预测。在这里,基于在云和边缘的XAI模型(例如,SHAP, LIME)提供的解释,我们的系统可以预测具有有效解释的受试者“心脏骤停”的可能性。这种类型的模型将是医疗保健行业的下一个重大升级,就自动化和一个自我解释的系统而言,它可以作为个人的个人健康助理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human-Centered Explainable AI at the Edge for eHealth
Explainable Artificial Intelligence (XAI) is a new paradigm of Artificial Intelligence (AI) that is giving different AI/ Machine Learning (ML) models a boost to penetrate sectors where people are thinking about adopting AI. This work focuses on the adoption of XAI in the health sector. It portrays that careful integration of XAI in both cloud and edge could change the whole healthcare industry and make humans more aware of their present health conditions, which is the need of the hour. To demonstrate the same, we have done an experiment based on the prediction of a particular medical condition called "cardiac arrest" in a specific subject group (patients who are 70 years old). Here, based on the explanation provided by the XAI model (e.g., SHAP, LIME) at Cloud and Edge, our system can predict the chances of a "cardiac arrest" for the subject with a valid explanation. This type of model will be the next big upgrade in the healthcare industry in terms of automation and a self-explanatory system that works as a personal health assistant for individuals.
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:604180095
Book学术官方微信