Imafidon, Chris and Kans, Aaron and Edoh, Aloysius (2009) ‘Human organ re-representation using UML and CMAUT’, Proceedings of Advances in Computing and Technology. (AC&T) The School of Computing and Technology 4th Annual Conference. University of East London, pp. 235-245.
Imafidon, C (2009) AC&T 235.pdf - Published Version
Available under License Creative Commons Attribution No Derivatives.
Download (455Kb) | Preview
Clinical data was captured and stored data using natural language (NL) in order to describe the human organs, their attributes and behaviour (Olsen et, 1998). Although this was an accurate form of data representation it created information overload, space complexity, inconsistency and erroneous data. To address the issue of data inconsistency and standardisation, clinical coding such as UMLS was used while for clinical interoperability and data exchange between users, NL7 was introduced. A survey conducted by (de Keizer et, 2000a) revealed that these methods are inadequate for clinical data representation hence the data rerepresentation technique (Haimowitz et, 1988) was introduced and used for modelling CIS with Entity Relationship Diagram (ERD) and (FOL)(de Keizer et, 2000b). However this model does not address the issue of information overload and space complexity. Hence, this paper presents an alternative approach where UML is used to capture human organs, their attributes and relationships. A new framework with built in algorithm converts the multiple attributes modelled in the class diagram into mathematical formalisation using the CMAUT. The logical expression serves as input to the optimisation algorithm to determine the optimal amount of data that must be retrieved for primary healthcare investigation. To evaluate the framework, mathematical operations were performed which revealed that the space complexity when using the CMA rerepresentation technique is θ ( n + 1) compared to θ (2n) for nonCMA. This means less space is needed when the CMA with AND connector is used but for substitutable organs with OR connector the space complexity for both CMA and nonCMA representations have the same exponential expansion of θ (2 n ). A ttest conducted on the amount of data required for investigation before and after optimisation gave a pvalue of 0.000 which means there is a significant different between the two data sets. For epidemiological analysis the output of the framework was benchmarked against the output of a web based heart risk calculator and the single sample ttest conducted gave a pvalue of 0.686 meaning there is no difference between two outputs. Thus this framework with data rerepresentation occupies less space as compared to others and can be used to calculate the risk factor of a heart patient.
|Item Type:||Conference or Event Item (Paper)|
|Additional Information:||Citation: Imafidon, C., Kans, A., Edoh, A. (2009) ‘Human organ re-representation using UML and CMAUT’ Proceedings of Advances in Computing and Technology, (AC&T) The School of Computing and Technology 4th Annual Conference, University of East London, pp.235-245.|
|Divisions:||Schools > Architecture Computing and Engineering, School of|
|Depositing User:||Mr Stephen Grace|
|Date Deposited:||02 Aug 2010 15:22|
|Last Modified:||27 Sep 2012 11:59|
Actions (login required)