Case based reasoning model in the diagnosis of psychiatric disorder
Preeti Bala Singh, Atma Prakash Singh, Shafeeq Ahmad · 2016
In the research area of medical computing; the diagnosis of psychiatric disorder is available in very few research work, books and journals etc. The diagnosis procedure of psychiatric disorder is very complicated and confusing. It was very difficult to diagnose psychiatric abnormality, by doctors, research groups and related agencies. The diagnosis process is very difficult in psychiatric disorder, so it is very difficult for the physician, research worker and other agencies to get the desired diagnosis method in the diagnosis of psychiatric disorder. The involvements of symptoms are vast in the diagnosis process and it makes diagnosis process complicated and difficult in psychiatric disorder diagnosis. Therefore, it is required to develop a model i.e. computer based model using software to address and solve the diagnosis problem in psychiatric disorder. This work focus on the design and development of case based reasoning model in the diagnosis of psychiatric disorder. Case based reasoning model implemented through several phases i.e. retrieval, reuse, revise and retention of the cases in the case base. The implementation of case based reasoning model starts with the retrieval. In retrieval, we are searching the stored cases for the new case. Matching is performed on the basis of similarity factor and the same is implemented through software. In this work, we are using 750 cases. Out of 750 cases, 500 cases used for case base creation and remaining 250 cases used for testing the proposed model. We are getting 96% accuracy for test cases. The main advantage of this model is to exploit the past knowledge for the new case and get implicit knowledge experience in the diagnosis of disorder.