医疗保健中的预测分析和预测建模

Sourav Mukherjee
{"title":"医疗保健中的预测分析和预测建模","authors":"Sourav Mukherjee","doi":"10.2139/ssrn.3403900","DOIUrl":null,"url":null,"abstract":"Predictive analytics looks forward trying to divine unknown future trials or actions based on data mining, statistics, modeling, deep learning and artificial intelligence, and machine learning. Business Intelligence, its forerunner in analytics, is a look backward. Predictive models are useful to business activities to well understand the customers, with the goal of forecasting buying patterns, potential risks, and its possible prospects. Healthcare industry organizes predictive analytics in different ways to improve operations and minimize risk. This article will explain the understanding of predictive analytics and predictive modeling, how the healthcare industry adopted predictive analytics and modeling and the importance of data mining in healthcare.","PeriodicalId":11036,"journal":{"name":"Demand & Supply in Health Economics eJournal","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Predictive Analytics and Predictive Modeling in Healthcare\",\"authors\":\"Sourav Mukherjee\",\"doi\":\"10.2139/ssrn.3403900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Predictive analytics looks forward trying to divine unknown future trials or actions based on data mining, statistics, modeling, deep learning and artificial intelligence, and machine learning. Business Intelligence, its forerunner in analytics, is a look backward. Predictive models are useful to business activities to well understand the customers, with the goal of forecasting buying patterns, potential risks, and its possible prospects. Healthcare industry organizes predictive analytics in different ways to improve operations and minimize risk. This article will explain the understanding of predictive analytics and predictive modeling, how the healthcare industry adopted predictive analytics and modeling and the importance of data mining in healthcare.\",\"PeriodicalId\":11036,\"journal\":{\"name\":\"Demand & Supply in Health Economics eJournal\",\"volume\":\"34 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Demand & Supply in Health Economics eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3403900\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Demand & Supply in Health Economics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3403900","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

摘要

预测分析是基于数据挖掘、统计学、建模、深度学习和人工智能以及机器学习,试图预测未知的未来试验或行动。作为分析学的先驱,商业智能是一种回顾。预测模型对业务活动非常有用,可以很好地了解客户,其目标是预测购买模式、潜在风险及其可能的前景。医疗保健行业以不同的方式组织预测分析,以改进操作并最大限度地降低风险。本文将解释对预测分析和预测建模的理解,医疗保健行业如何采用预测分析和建模,以及数据挖掘在医疗保健中的重要性。
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
Predictive Analytics and Predictive Modeling in Healthcare
Predictive analytics looks forward trying to divine unknown future trials or actions based on data mining, statistics, modeling, deep learning and artificial intelligence, and machine learning. Business Intelligence, its forerunner in analytics, is a look backward. Predictive models are useful to business activities to well understand the customers, with the goal of forecasting buying patterns, potential risks, and its possible prospects. Healthcare industry organizes predictive analytics in different ways to improve operations and minimize risk. This article will explain the understanding of predictive analytics and predictive modeling, how the healthcare industry adopted predictive analytics and modeling and the importance of data mining in healthcare.
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
Procurement Institutions and Essential Drug Supply in Low and Middle-Income Countries Watching the Grass Grow: Does Recreational Cannabis Legalization Affect Labor Outcomes? Decomposition of Clinical Disparities with Machine Learning Economic Consequences of Hospital Closures The Price-Leverage Covariation as a Measure of the Response of the Leverage Effect To Price and Volatility Changes
×
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