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

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No
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Top 10%
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Top 10%
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Top 10%

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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
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OpenCitations Citation Count
13

Source

Journal of Intelligent & Fuzzy Systems

Volume

33

Issue

4

Start Page

2007

End Page

2017

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Citations

CrossRef : 13

Scopus : 13

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Mendeley Readers : 16

SCOPUS™ Citations

13

checked on Feb 09, 2026

Web of Science™ Citations

7

checked on Feb 09, 2026

Page Views

1

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