@article{MAKHILLAJIT2006545110,
    title = {Data Mining Approach to Cervical Cancer Patients Analysis Using Clustering Technique},
    journal = {Asian Journal of Information Technology},
    volume = {5},
    number = {4},
    pages = {413-417},
    year = {2006},
    issn = {1682-3915},
    doi = {ajit.2006.413.417},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2006.413.417},
    author = {Kuttiannan Thangavel,P. Palanichamy Jaganathan and},
    keywords = {Data mining,cervical cancer,patterns,knowledge discovery,clustering,k-means},
    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.}
    }