|Affiliations:||Mathematical Institute of the Serbian Academy of Sciences and Arts||Title:||Transforming electronic medical books to diagnostic decision support systems using relational database management systems||First page:||79||Last page:||103||Related Publication(s):||Computational Medicine in Data Mining and Modeling||Issue Date:||1-Dec-2013||Rank:||M14||ISBN:||978-1-4614-8784-5||DOI:||10.1007/978-1-4614-8785-2_3||Abstract:||
The aim of this study was to analyse possibility of developing diagnostic decision support systems (DDSS) from electronic books. Analysis of typical text in major textbooks was performed, and basic structural forms were determined. Knowledge-based DDSS are proposed trying to adapt to the structure of the data and 'natural' logic of medical books. We propose a method for transforming a major textbook (with numerous editions) into a simple knowledge-based model of DDSS that authors and editors of the book can easily understand. Structure of the knowledge base includes at least 'Disease', 'Finding', 'Relation' and 'Thesaurus' tables. Probability of findings and relations could be expressed as sensitivity, specificity and predictive value. The authors of the book may be kindly asked to use already prepared application and present facts in form of 'diseases', 'findings' and 'relations on sets of findings' when they prepare the text of a book. Maintenance and update of DDSS would be related to the new edition of the book. DDSS would be linked to the electronic text of the book and could be also linked to a local information system. In this way we believe that the proposed model of DDSS would be a stimulus for further development of clinical decision support systems that may be interesting for many readers of the books in which they trust for large number of editions.
|Keywords:||Clinical decision support systems | Diagnostic decisions | Electronic books | Knowledge-based model | Local information systems | Predictive values | Relational database management systems||Publisher:||Springer Link|
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