Model, based on computing with words and competitive fuzzy cognitive maps, for the representation of the interrelationships between symptoms, signs and cardiovascular diseases
DOI:
https://doi.org/10.53591/iti.v6i6.1204Keywords:
computing with words, fuzzy cognitive maps, granularity, medical diagnosisAbstract
Fuzzy cognitive maps have received increasing attention for the representation of the causal knowledge, due to its especial use fulness in medical diagnosis . This paper proposes a representation of interrelations among symptoms, signs and cardiac diseases based on competitive fuzzy cognitive maps, using the paradigm of Computing with Words, in order to provide causal models easy to understand. To this end, the use of linguistic representation model based on linguistic 2-tuple in the competitive fuzzy cognitive maps is proposed, which allowing to perform the Computing with Words Processes without losing information. As a result of this paper, a new model of fuzzy cognitive maps is obtained, which is called Linguistic Competitive Fuzzy Cognitive Map (LCFCM). The main advantage of the model proposed for medical diagnosis, based on fuzzy cognitive maps, is that it allows increasing the interpretability of the causal models, being this fact useful in medical diagnosis. Last, the paper presents a case study of the model proposed and a static analysis of this model to determine symptoms and s ig ns more important in the map obtained, as well as recommendations for future works.
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Copyright (c) 2014 Salah Hasan Saleh, Maikel Yelandi Leyva Vázquez, Juan Pedro Febles Rodríguez, Fawaz Saleem Mohsen
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