{"title":"介绍临床数据挖掘的特殊部分","authors":"Shipeng Yu, R. B. Rao","doi":"10.1145/2408736.2408738","DOIUrl":null,"url":null,"abstract":"Mining clinical data is a fast-evolving field, ranging from mining patient data of a particular type (e.g., images, genomics) to mining the increased amount of mixed-format information (databases, free text, images, labs, etc) in electronic health records (EHR), to selecting, extracting and synthesizing relevant knowledge from large medical corpuses, to the promise of personalized medicine where therapy and prevention are tailored to smaller and smaller patient subpopulations, down to the individual patient. Clinical data mining can be a key asset in driving vast systemic improvements in healthcare, leading to improved patient outcomes and reduced healthcare costs. In this report we briefly survey the latest advancements in this field, and introduce four selected articles that cover both state-of-the-art data mining techniques for clinical data and discuss emerging clinical data mining applications.","PeriodicalId":90050,"journal":{"name":"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining","volume":"16 1","pages":"1-3"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Introduction to the special section on clinical data mining\",\"authors\":\"Shipeng Yu, R. B. Rao\",\"doi\":\"10.1145/2408736.2408738\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mining clinical data is a fast-evolving field, ranging from mining patient data of a particular type (e.g., images, genomics) to mining the increased amount of mixed-format information (databases, free text, images, labs, etc) in electronic health records (EHR), to selecting, extracting and synthesizing relevant knowledge from large medical corpuses, to the promise of personalized medicine where therapy and prevention are tailored to smaller and smaller patient subpopulations, down to the individual patient. Clinical data mining can be a key asset in driving vast systemic improvements in healthcare, leading to improved patient outcomes and reduced healthcare costs. In this report we briefly survey the latest advancements in this field, and introduce four selected articles that cover both state-of-the-art data mining techniques for clinical data and discuss emerging clinical data mining applications.\",\"PeriodicalId\":90050,\"journal\":{\"name\":\"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining\",\"volume\":\"16 1\",\"pages\":\"1-3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2408736.2408738\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2408736.2408738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Introduction to the special section on clinical data mining
Mining clinical data is a fast-evolving field, ranging from mining patient data of a particular type (e.g., images, genomics) to mining the increased amount of mixed-format information (databases, free text, images, labs, etc) in electronic health records (EHR), to selecting, extracting and synthesizing relevant knowledge from large medical corpuses, to the promise of personalized medicine where therapy and prevention are tailored to smaller and smaller patient subpopulations, down to the individual patient. Clinical data mining can be a key asset in driving vast systemic improvements in healthcare, leading to improved patient outcomes and reduced healthcare costs. In this report we briefly survey the latest advancements in this field, and introduce four selected articles that cover both state-of-the-art data mining techniques for clinical data and discuss emerging clinical data mining applications.