Classification of Clinical Dataset of Cervical Cancer using KNN
Classification of Clinical Dataset of Cervical Cancer using KNN
复制标题
使用 KNN 对宫颈癌临床数据集进行分类
DOI：
10.17485/ijst/2016/v9i28/98380
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Vishu Madaan
中科院分区：
文献类型：
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作者：
Meenakshi Sharma;Sanjay Kumar Singh;Prateek Agrawal;Vishu Madaan
Background/Objectives: The primary objective of this paper is to classify the clinical dataset of cervical cancer to identify the stage of cancer which helps in proper treatment of patient suffering from cancer. Methods/Statistical Analysis: This research work basically moves toward the detection of cervical cancer using Pap smear images. Analysis of Pap smear of cervical region is an efficient technique to study any abnormality in cervical cells. The proposed system firstly segment the pap image using Edge Detection to separate the cell nuclei from cytoplasm and background and then extract various features of cervical pap images like area, perimeter, elongation and then these features are normalized using min-max method. After normalization KNN method is used to classify cancer according to its abnormality. Findings: The classification accuracy with 84.3% of maximum performance with no validation and classification accuracy with 82.9% of maximum performance with 5 Fold cross validation is achieved.
