使用机器学习算法预测疾病的分析方法

Ayushi Grover, Anukriti Kalani, S. Dubey
{"title":"使用机器学习算法预测疾病的分析方法","authors":"Ayushi Grover, Anukriti Kalani, S. Dubey","doi":"10.1109/Confluence47617.2020.9058120","DOIUrl":null,"url":null,"abstract":"Healthcare is a human right and in this complex technology driven world, healthcare industry is equipped with modern technology for the solution of disease but struggles when it comes to prevent them beforehand. Machine learning can transform healthcare industry. Machine Learning provides a wide scope of apparatuses, strategies and structures to address difficulties like electronic record the executives, information combination, PC supported judgments and disease expectation. This research paper aims to predict disease accurately according to the symptoms of patients and helps doctor in better diagnosis, further reducing the cost of treatment and improving quality of life. It includes the comparative study of the outcomes and time required for analysis and prediction of disease by various machine learning algorithms and contribute towards research in healthcare department.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Analytical Approach towards Prediction of Diseases Using Machine Learning Algorithms\",\"authors\":\"Ayushi Grover, Anukriti Kalani, S. Dubey\",\"doi\":\"10.1109/Confluence47617.2020.9058120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Healthcare is a human right and in this complex technology driven world, healthcare industry is equipped with modern technology for the solution of disease but struggles when it comes to prevent them beforehand. Machine learning can transform healthcare industry. Machine Learning provides a wide scope of apparatuses, strategies and structures to address difficulties like electronic record the executives, information combination, PC supported judgments and disease expectation. This research paper aims to predict disease accurately according to the symptoms of patients and helps doctor in better diagnosis, further reducing the cost of treatment and improving quality of life. It includes the comparative study of the outcomes and time required for analysis and prediction of disease by various machine learning algorithms and contribute towards research in healthcare department.\",\"PeriodicalId\":180005,\"journal\":{\"name\":\"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Confluence47617.2020.9058120\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Confluence47617.2020.9058120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

医疗保健是一项人权,在这个复杂的技术驱动的世界里,医疗保健行业配备了现代技术来解决疾病,但在事先预防疾病方面却很困难。机器学习可以改变医疗保健行业。机器学习提供了广泛的设备、策略和结构来解决诸如电子记录高管、信息组合、PC支持的判断和疾病预期等难题。本研究旨在根据患者的症状准确预测疾病,帮助医生更好地诊断,进一步降低治疗成本,提高生活质量。它包括通过各种机器学习算法分析和预测疾病所需的结果和时间的比较研究,并为医疗保健部门的研究做出贡献。
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
Analytical Approach towards Prediction of Diseases Using Machine Learning Algorithms
Healthcare is a human right and in this complex technology driven world, healthcare industry is equipped with modern technology for the solution of disease but struggles when it comes to prevent them beforehand. Machine learning can transform healthcare industry. Machine Learning provides a wide scope of apparatuses, strategies and structures to address difficulties like electronic record the executives, information combination, PC supported judgments and disease expectation. This research paper aims to predict disease accurately according to the symptoms of patients and helps doctor in better diagnosis, further reducing the cost of treatment and improving quality of life. It includes the comparative study of the outcomes and time required for analysis and prediction of disease by various machine learning algorithms and contribute towards research in healthcare department.
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
期刊最新文献
Identification of the most efficient algorithm to find Hamiltonian Path in practical conditions Segmentation and Detection of Road Region in Aerial Images using Hybrid CNN-Random Field Algorithm A Novel Approach for Isolation of Sinkhole Attack in Wireless Sensor Networks Performance Analysis of various Information Platforms for recognizing the quality of Indian Roads Time Series Data Analysis And Prediction Of CO2 Emissions
×
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