{"title":"Exploratory and directed analysis of medical information via dynamic classification trees","authors":"C. Hughes","doi":"10.1109/ECBS.1988.5457","DOIUrl":null,"url":null,"abstract":"Medical data are often voluminous, incomplete, and nonnumeric, making analysis with traditional statistical techniques difficult at best. A generic medical data-analysis system called FRID (finding rules in data), which can handle this type of data, is proposed. Incorporating partitioning heuristics, FRID can be used to initiate broad-based exploratory analysis. The system's flexible design also allows a specific search for the probability of a disease given a single symptom. Results from experiments using this system are presented, as well as plans for its future use.<<ETX>>","PeriodicalId":291071,"journal":{"name":"Proceedings of the Symposium on the Engineering of Computer-Based Medical","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Symposium on the Engineering of Computer-Based Medical","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECBS.1988.5457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Medical data are often voluminous, incomplete, and nonnumeric, making analysis with traditional statistical techniques difficult at best. A generic medical data-analysis system called FRID (finding rules in data), which can handle this type of data, is proposed. Incorporating partitioning heuristics, FRID can be used to initiate broad-based exploratory analysis. The system's flexible design also allows a specific search for the probability of a disease given a single symptom. Results from experiments using this system are presented, as well as plans for its future use.<>
医疗数据通常是大量的、不完整的和非数字的，这使得用传统的统计技术进行分析变得困难。提出了一种能够处理这类数据的通用医疗数据分析系统，称为FRID (finding rules in data)。结合划分启发式，FRID可用于发起广泛的探索性分析。该系统灵活的设计还允许对给定单一症状的疾病概率进行特定搜索。本文给出了该系统的实验结果，并对其未来的应用进行了展望。
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