An intelligent model for two level diagnoses of neuromuscular diseases
Babita Pandey, R. B. Mishra · International Journal of Knowledge Engineering and Soft Data Paradigms · 2014
In this paper, we have developed a intelligent model that performs two level diagnosis of neuromuscular diseases (NMDs) by using muscular, cognitive, psychological, internal lingual and EMG parameters. At first level, the NMDs are: muscular dystrophy, polymyositis, endocrine myopathy, metabolic myopathy, neuropathy, poliomyelitis and myasthenia gravis. These diseases are further classified in more specific diseases at second level. Data mining methods are used to obtain the important parameters/symptoms. A hierarchal rule base model is integrated with case base reasoning for calculating cumulative confidence factor (CCF) and confidence index. In addition to this a Bayesian network (BN) model is also developed for calculating the probability of occurrence of diseases and to make a comparative view of the results obtained by CCF and BN approaches.