Diagnosing skin diseases using an artificial neural network

Abstract

Development of medical expert systems that use artificial neural networks as their knowledge bases appears to be a promising method for predicting diagnosis and possible treatment routine. This paper deals with the construction and training of an artificial neural network for skin disease diagnosis (SDD) based on patients' symptoms and causative organisms. The artificial neural network constructed using a feed-forward architectural design is shown to be capable of successfully diagnosing selected skin diseases in the tropical areas such as Nigeria with 90 percent accuracy. The work may in the future serve as a knowledge base for an expert system specializing in medical diagnosis, testing evaluation, treatment evaluation, and treatment effectiveness. The work serves as the first component of a much larger system that will assist physicians facilitate the reasonable ordering of tests and treatments and minimize unnecessary laboratory routines while reducing operational costs.