An Expert System for the Diagnosis of Sexually Transmitted Diseases - Esstd

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Green Open Access

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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

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OpenCitations Citation Count
13

Volume

33

Issue

4

Start Page

2007

End Page

2017

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Citations

CrossRef : 12

Scopus : 13

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Mendeley Readers : 16

SCOPUS™ Citations

13

checked on Jun 04, 2026

Web of Science™ Citations

7

checked on Jun 04, 2026

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2.53

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