Fuzzy Analysis of Breast Cancer Disease using Fuzzy c-means and Pattern Recognition

Fuzzy Analysis of Breast Cancer Disease using Fuzzy c-means and Pattern Recognition

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. The automatic diagnosis of breast cancer is an important, real-world medical problem. In this article is introduced a new approach for diagnosis of breast cancer. The proposed approach uses Fuzzy c-means (FCM) algorithm and patter...

Pattern Recognition using the Fuzzy c-means Technique

In the field of pattern recognition due to the fundamental involvement of human perception and inadequacy of standard Mathematics to deal with its complex and ambiguously defined system, different fuzzy techniques have been applied as an appropriate alternative. A pattern recognition system has to undergo basically the steps of preprocessing, feature extraction and selection, classifier design ...

Diagnosis of Parkinson’s Disease using Fuzzy C-Means Clustering and Pattern Recognition

Parkinson’s disease (PD) is a global public health problem of enormous dimension. In this study, we aimed to discriminate between healthy people and people with Parkinson’s disease (PD). Various studies revealed, that voice is one of the earliest indicator of PD, and for that reason, Parkinson dataset that contains biomedical voice of human is used. The main goal of this paper is to automatical...

Detect Breast Cancer using Fuzzy C means Techniques in Wisconsin Prognostic Breast Cancer (WPBC) Data Sets

Medical data mining is very much valuable to medical experts. The main task of data mining is diagnosing the patient’s disease Classification. Breast cancer is a severe and life threatening disease very commonly found in woman. An unusual growth of cells in breast is the main source of breast cancer those cells can be of two types malignant (Cancerous) and benign (Non-Cancerous) these types mus...

Bulgarian Hand-Printed Character Recognition Using Fuzzy C-Means Clustering