Early Diagnosis of Lung Cancer with ANN, FCM and FMNN

Asian Countries like India, Pakistan, Bhutan, Bangladesh, Nepal and Sri Lanka are having their approximate total population of more than 1,500 million. In spite of enormous diversity in their demographic information, there are number of similar parameters causing to cancer. Oral cancer and lung cancer in males are noted as a few numbers, depending on its registry [15]. Uncontrolled cell progress in lung tissues causes lung cancer disease. It is the most frequent incurable malignancy in both men and women. Lung cancer can completely recover by early detection and treatment survived patient. Artificial Neural Network (ANN), Fuzzy C-Mean (FCM) and Fuzzy Min-Max Neural network (FMNN) are very effective and helpful in cancer diagnosis for its several advantages. The motive behind that the fault tolerance, flexibility, non linearity are the factors of artificial neural network. In case of FCM, it provides finest findings for overlapped data set; data point may be connected with more then one cluster centre. Non-linear separability, soft and hard decision, less training time, online adaptation is the advantages of FMNN. In this paper the author suggest using FCM and FMNN to diagnose lung cancer. Keywords— Artificial Neural Network (ANN), Fuzzy C-Mean (FCM), Fuzzy Min-Max Neural Network (FMNN) Classification and Clustering