Multiple fuzzy c-means clustering algorithm in medical diagnosis.

Background: In recent years, the use of the fuzzy c-means (FCM) clustering techniques in medical diagnosis has steadily increased, because of its effectiveness in recognizing systems in the medical database to help medical experts diagnosing diseases. However, its performance is highly dependent on the randomly initialized cluster centroids which may allow the diagnosis to be trapped into the problem of the local optimum.

Objective: This paper proposes a multiple fuzzy c-means (MFCM) algorithm for medical diagnosis.