Pub Date : 2015-10-01DOI: 10.1109/SIBIRCON.2015.7361885
V. Malykh, D. Belyshev
This study describes an approach to building a clinical data bank on the basis of a standardized clinical process model. A clinical data bank is considered as a repository of clinical cases, which is medical knowledge reflecting both up-to-date and retrospective medical data. In view of the case-based nature of the decision making process in medicine, a clinical data bank can be used in clinical processes to make diagnosis and treatment decisions. The study discusses the following issues: a) choosing an approach to modeling a clinical process; b) completeness of the model; c) medical data standardization and normalization; d) plain medical text mining; d) big medical data analysis. The study also looks at metric-based methods of searching for relevant clinical cases in the data bank.
{"title":"Case-based reasoning in clinical processes using clinical data banks","authors":"V. Malykh, D. Belyshev","doi":"10.1109/SIBIRCON.2015.7361885","DOIUrl":"https://doi.org/10.1109/SIBIRCON.2015.7361885","url":null,"abstract":"This study describes an approach to building a clinical data bank on the basis of a standardized clinical process model. A clinical data bank is considered as a repository of clinical cases, which is medical knowledge reflecting both up-to-date and retrospective medical data. In view of the case-based nature of the decision making process in medicine, a clinical data bank can be used in clinical processes to make diagnosis and treatment decisions. The study discusses the following issues: a) choosing an approach to modeling a clinical process; b) completeness of the model; c) medical data standardization and normalization; d) plain medical text mining; d) big medical data analysis. The study also looks at metric-based methods of searching for relevant clinical cases in the data bank.","PeriodicalId":6503,"journal":{"name":"2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON)","volume":"24 1","pages":"211-216"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83261493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-10-01DOI: 10.1109/SIBIRCON.2015.7361867
V. Kolosov, N. Bezrukov, Denis Naumov, Yuliy M. Perelman, A. Prikhodko
The paper discusses the development of decision support systems based on adaptive neuro-fuzzy network to predict the osmotic airway hyperreactivity in patients with bronchial asthma. Static spirography data analysis has been conducted and polymorphism in the TRPV4 gene examined. A prediction system comprising the parts of pre-processing and neuro-fuzzy inference has been developed. A GUI has been implemented for the system. MATLAB is used as the modeling and computation engine.
{"title":"Prediction of osmotic airway hyperresponsiveness in patients with bronchial asthma using adaptive neuro-fuzzy network","authors":"V. Kolosov, N. Bezrukov, Denis Naumov, Yuliy M. Perelman, A. Prikhodko","doi":"10.1109/SIBIRCON.2015.7361867","DOIUrl":"https://doi.org/10.1109/SIBIRCON.2015.7361867","url":null,"abstract":"The paper discusses the development of decision support systems based on adaptive neuro-fuzzy network to predict the osmotic airway hyperreactivity in patients with bronchial asthma. Static spirography data analysis has been conducted and polymorphism in the TRPV4 gene examined. A prediction system comprising the parts of pre-processing and neuro-fuzzy inference has been developed. A GUI has been implemented for the system. MATLAB is used as the modeling and computation engine.","PeriodicalId":6503,"journal":{"name":"2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON)","volume":"44 1","pages":"130-133"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84189204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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