Design and implementation of a muscleskeletal disorder diagnosis using expert systems

Description

Abstract This project centers around concepts of prediction through algorithms. In this case, we would be employing expert systems to predict muscle disorders using the most common symptoms. Expert systems have been around since the 1970s and emulate the decision-making of a human expert basically and in this case, disease diagnosis. This project centers around both a new diagnosis system and an existing diagnosis system. For the existing one, we want to optimize the features of the current system and include a fully automated capability. This is proposed to be done by having guest accounts with medical records. The project goes through a rigorous and thorough software development cycle which in this case makes use of the Waterfall model. We lay down the software design principles and strategies to make it a secure one.