Mısra, SanjayThompson, TemitopeSowunmi, OlaperiMisra, SanjayFernandez-Sanz, LuisCrawford, BroderickSoto, RicardoComputer Engineering2024-07-052024-07-05201771064-12461875-896710.3233/JIFS-1612422-s2.0-85029906846https://doi.org/10.3233/JIFS-161242https://hdl.handle.net/20.500.14411/612Misra, Sanjay/0000-0002-3556-9331; Fernandez-Sanz, Luis/0000-0003-0778-0073; Okuboyejo, Olaperi/0000-0002-0937-2607Over 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.eninfo:eu-repo/semantics/closedAccessArtificial intelligencerule-based expert systemsknowledge basedecision treessexually transmitted diseasesArticleQ4Q333420072017WOS:000411449700003