{"title":"A representational analysis of a temporal indeterminancy display in clinical events","authors":"M. Madkour, Hsing-yi Song, Jingcheng Du, Cui Tao","doi":"10.1109/BIBM.2016.7822673","DOIUrl":null,"url":null,"abstract":"This paper describes a proposition for representing temporal indeterminacy in events from clinical narratives using fuzzy sets membership functions. This approach leverages both temporal and semantic information of events and has been proved by representational analysis evaluation method. We demonstrate that membership functions' graphs can be used for representing temporal approximation and granularity of events. We also show that this approach is helpful for the construction of fine timeline of clinical events, and can be used for calculating accurate metrics for ordering events.","PeriodicalId":345384,"journal":{"name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2016.7822673","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
This paper describes a proposition for representing temporal indeterminacy in events from clinical narratives using fuzzy sets membership functions. This approach leverages both temporal and semantic information of events and has been proved by representational analysis evaluation method. We demonstrate that membership functions' graphs can be used for representing temporal approximation and granularity of events. We also show that this approach is helpful for the construction of fine timeline of clinical events, and can be used for calculating accurate metrics for ordering events.