Skin infection detection using Dempster-Shafer theory

Skin infections still remain common in many rural communities in developing countries, with serious economic and social consequences as well as health implications. Directly or indirectly, skin infections are responsible for much disability (and loss of economic potential), disfigurement, and distress due to symptoms such as itching or pain. In this research, we built a Skin Infection Expert System for detecting skin infections and displaying the result of detection process. We describe five symptoms as major symptoms which include blister, itch, scaly skin, fever, and pain in the rash. Dempster-Shafer theory to quantify the degree of belief as inference engine in expert system, our approach uses Dempster-Shafer theory to combine beliefs under conditions of uncertainty and ignorance, and allows quantitative measurement of the belief and plausibility in our identification result.