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A decision support system for diagnosis of rheumatic fever in Nepal

A decision support system for diagnosis of rheumatic fever in Nepal

Pandey, Sanjib Raj, Njovu, Chiyaba and Lai, Choi-Hong ORCID: 0000-0002-7558-6398 (2012) A decision support system for diagnosis of rheumatic fever in Nepal. In: 7th Asia Pacific Medical Informatics Conference, 22-25 Oct 2012, Beijing, China. (Unpublished)

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Abstract

Rheumatic Heart Disease (RHD) is one of the major diseases leading to premature deaths of children in Nepal. The cause of RHD is untreated or late diagnosis of Rheumatic Fever (RF). Efforts aimed at preventing RHD in Nepal have been hampered by poor infrastructure in various parts of the country. In this paper we propose a Decision Support System (DSS) to be used by medical practitioners in the diagnosis of RF/RHD. Our proposed system incorporates a knowledge base which can be used by doctors to diagnose RF in its early stages thereby preventing many cases of RHDs. We describe a new approach for diagnosing RF in four different categories. These categories describe the severity of the disease according to the recorded symptoms. We define the severity of RF into either Suspected, Mild, Moderate and Severe. Our proposed system is designed to provide initial support for the rural health workers or inexperienced doctors to diagnose RF in its early stages.

Item Type: Conference or Conference Paper (Paper)
Additional Information: [1] This paper was first presented at the 7th Asia Pacific Medical Informatics Conference, (APAMI 2012) held from 24-25 October 2012 in Beijing, China. The paper was given on 24 October 2012 within the Intelligent Analysis and Image Processing Section.
Uncontrolled Keywords: rheumatic fever, knowledge-base, rules, WHF, WHO's criteria, local country guidelines, decision support system
Subjects: Q Science > QA Mathematics > QA76 Computer software
R Medicine > R Medicine (General)
Pre-2014 Departments: School of Computing & Mathematical Sciences
Related URLs:
Last Modified: 14 Oct 2016 09:24
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/9934

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