Title: A CBR system for diabetes mellitus diagnosis: case-base standard data model

Authors: Shaker El-Sappagh; Mohammed Elmogy; Alaa Eldin M. Riad

Addresses: Faculty of Computes and Information, Minia University, Egypt ' Faculty of Computes and Information, Minia University, Egypt ' Faculty of Computes and Information, Minia University, Egypt

Abstract: Diabetes is the sixth chronic disease causing death all over the world. The early diagnosis of diabetes is a critical step in diabetes care process. Clinical decision support system (CDSS) based on case-based reasoning (CBR) helps in early detection and diagnosis of diabetes. Building CBR's case-base knowledge is the most critical challenge. On the other hand, electronic health record (EHR) is considered as the complete source of patient cases. This paper proposes a standard case-base relational data model for diabetes diagnosis based on HL7 RIM, EHR, and SNOMED CT. This model will collect all patient clinical data from distributed EHRs, and it will formulate it in the form of problem-solution. This case-base knowledge will be used as the knowledge base for a diabetes diagnosis CBR system.

Keywords: case-based reasoning; CBR; clinical DSS; decision support systems; CDSS; diabetes mellitus diagnosis; electronic health records; EHR; HL7 RIM; early detection; diabetes diagnosis; knowledge base.

DOI: 10.1504/IJMEI.2015.070116

International Journal of Medical Engineering and Informatics, 2015 Vol.7 No.3, pp.191 - 208

Received: 30 May 2014
Accepted: 22 Jul 2014
Published online: 27 Jun 2015 *

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