TY  - JOUR
T1  - Data Mining Approach to Cervical Cancer Patients Analysis Using Clustering Technique
AU - , Kuttiannan Thangavel AU - , P. Palanichamy Jaganathan AU - , P.O. Easmi 
JO  - Asian Journal of Information Technology
VL  - 5
IS  - 4
SP  - 413
EP  - 417
PY  - 2006
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2006.413.417
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2006.413.417
KW  - Data mining
KW  -cervical cancer
KW  -patterns
KW  -knowledge discovery
KW  -clustering
KW  -k-means
AB  - 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.
ER  -