{"title":"Modelling Diseases with Stream X-Machine","authors":"S. Jayatilake, E. Ogunshile, M. Aydin, K. Phung","doi":"10.1109/CONISOFT52520.2021.00020","DOIUrl":null,"url":null,"abstract":"At present the world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accuracy is demanded. Formal methods have been proven to be occupied in critical system development. This paper introduces a generic disease model called Stream X-Machine Disease Model (SXMDM) based on X-Machine theory. SXMDM has been developed as a proof of concept that formal methods, especially Stream X-Machines, can be employed to model medical conditions or diseases. We have conducted an experiment on modelling an actual disease using a case study of type 2 diabetes. The results of the experiment illustrates that the proposed SXMDM is capable of modelling chronic diseases.","PeriodicalId":380632,"journal":{"name":"2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 9th International Conference in Software Engineering Research and Innovation (CONISOFT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONISOFT52520.2021.00020","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
At present the world is moving towards alternative medicine and behavioural alteration for treating, managing, and preventing chronical diseases. With the individuality of the human beings has added more complexity in a domain where very high accuracy is demanded. Formal methods have been proven to be occupied in critical system development. This paper introduces a generic disease model called Stream X-Machine Disease Model (SXMDM) based on X-Machine theory. SXMDM has been developed as a proof of concept that formal methods, especially Stream X-Machines, can be employed to model medical conditions or diseases. We have conducted an experiment on modelling an actual disease using a case study of type 2 diabetes. The results of the experiment illustrates that the proposed SXMDM is capable of modelling chronic diseases.
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