An Expert System for the Diagnosis of Sexually Transmitted Diseases - Esstd
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
Ios Press
Open Access Color
Green Open Access
No
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
Over 93 million people get ill with sexually transmitted diseases in sub-Saharan Africa. However, research has shown that people with sexually transmitted diseases find it difficult to share their problem with a physician due to societal discrimination in Africa. Due to this problem, we have implemented a medical expert system for diagnosing sexually transmitted diseases (ESSTD) that maintains the anonymity of the individuals. The patients diagnose themselves by answering questions provided by the system. This paper presents the design and development of the system. Forward chaining rules were used to implement the knowledge base and the system is easily accessible on mobile platforms. The Java Expert System Shell was used for its inference engine and the system was validated by domain experts. It is useful because it helps to maintain anonymity for patients with STD.
Description
Misra, Sanjay/0000-0002-3556-9331; Fernandez-Sanz, Luis/0000-0003-0778-0073; Okuboyejo, Olaperi/0000-0002-0937-2607
Keywords
Artificial intelligence, rule-based expert systems, knowledge base, decision trees, sexually transmitted diseases
Fields of Science
0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
WoS Q
Q4
Scopus Q
Q2

OpenCitations Citation Count
13
Source
Journal of Intelligent & Fuzzy Systems
Volume
33
Issue
4
Start Page
2007
End Page
2017
PlumX Metrics
Citations
CrossRef : 13
Scopus : 13
Captures
Mendeley Readers : 16
SCOPUS™ Citations
13
checked on Feb 09, 2026
Web of Science™ Citations
7
checked on Feb 09, 2026
Page Views
1
checked on Feb 09, 2026
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