Disease Diagnosis using Soft Computing Model: A Digest

Abstract

In today's era, medical diagnosis has become one of the most progressive disciplines. Since people are taking hybrid food in the daily life, different disease came into existence. It made people very careful for their health. In some cases, lack of knowledge of disease in doctor causes the patient death. Therefore, we require such diagnosis system for non-expertise so that right prescription can come for the patient. Over the years, soft computing plays the major role for computer aided disease diagnosis in physician decision process. Considering these issues, a lot work has been devoted to this discipline. Several disease diagnosis systems based on fuzzy, rule based reasoning, case based reasoning etc. have been proposed for different disease using their symptoms. Hepatitis diagnosis system is good example which is based on CBR. In this paper, we reviewed such types of diagnosis system and their techniques used. We also emphasizes on the liver disease diagnosis system. Moreover, we also found shortcoming in the present systems that cause the vague diagnosis system. Hence, patient gets more illness or sometimes costs as death. We also directed future work that will help to make the present system more robust, reliable, and helpful for nonexpertise.

Wrapper-Based Feature Selection to Classify Flatfoot Disease

“…Nowadays, computational intelligence has been applied in different medical areas for classification, clustering, and feature selection tasks [12], [13]. There are techniques based on fuzzy cognitive maps (FCM) trained by genetic algorithms (GA) and multi-layer perceptron (MLP) neural networks, which try to predict the classification of human plantar foot disorders (flatfoot and cavus foot) [14].…”