Comput Math Methods Med - Feature selection for better identification of subtypes of Guillain-Barr? syndrome.

Tópicos

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{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Guillain-Barr? syndrome (GBS) is a neurological disorder which has not been explored using clustering algorithms. Clustering algorithms perform more efficiently when they work only with relevant features. In this work, we applied correlation-based feature selection (CFS), chi-squared, information gain, symmetrical uncertainty, and consistency filter methods to select the most relevant features from a 156-feature real dataset. This dataset contains clinical, serological, and nerve conduction tests data obtained from GBS patients. The most relevant feature subsets, determined with each filter method, were used to identify four subtypes of GBS present in the dataset. We used partitions around medoids (PAM) clustering algorithm to form four clusters, corresponding to the GBS subtypes. We applied the purity of each cluster as evaluation measure. After experimentation, symmetrical uncertainty and information gain determined a feature subset of seven variables. These variables conformed as a dataset were used as input to PAM and reached a purity of 0.7984. This result leads to a first characterization of this syndrome using computational techniques.

Resumo Limpo

guillainbarr syndrom gbs neurolog disord explor use cluster algorithm cluster algorithm perform effici work relev featur work appli correlationbas featur select cfs chisquar inform gain symmetr uncertainti consist filter method select relev featur featur real dataset dataset contain clinic serolog nerv conduct test data obtain gbs patient relev featur subset determin filter method use identifi four subtyp gbs present dataset use partit around medoid pam cluster algorithm form four cluster correspond gbs subtyp appli puriti cluster evalu measur experiment symmetr uncertainti inform gain determin featur subset seven variabl variabl conform dataset use input pam reach puriti result lead first character syndrom use comput techniqu

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