Breast-cancer identification using HMM-fuzzy approach.

This paper presents an ensemble of feature selection and classification technique for classifying two types of breast lesion, benign and malignant. Features are selected based on their area under the ROC curves (AUC) which are then classified using a hybrid hidden Markov model (HMM)-fuzzy approach. HMM generated log-likelihood values are used to generate minimized fuzzy rules which are further optimized using gradient descent algorithms in order to enhance classification performance.