Abstract: Data mining is an umbrella term referring to the process of discovering patterns in data, typically with the aid of powerful algorithms to automate part of the search. These methods come from the disciplines such as statistics, machine learning (Artificial Intelligence), pattern recognition, neural networks and databases. In particular this paper reveals out how the problem of cervical cancer diagnosis is approached by a data mining analyst with a background in machine learning. Application areas for this problem include analysis of telecommunications systems, discovering frequent buying patterns, analysis of patient`s medical records, etc. In the health field, data mining applications have been growing considerably as it can be used to directly derive patterns, which are relevant to forecast different risk groups among the patients. To the best of our knowledge data mining technique such as clustering has not been used to analyse cervical cancer patients. Hence, in this paper we made an attempt to identify patterns from the database of the cervical cancer patients using clustering.
Kuttiannan Thangavel , P. Palanichamy Jaganathan and P.O. Easmi , 2006. Data Mining Approach to Cervical Cancer Patients Analysis Using Clustering Technique. Asian Journal of Information Technology, 5: 413-417.