Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier-Reference-Cited by-同舟云学术

Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier

Published:2019-07-17 Issue:9 Volume:43 Page:
ISSN:0148-5598
Container-title:Journal of Medical Systems
language:en
Short-container-title:J Med Syst

Author:

Geetha R.,Sivasubramanian S.,Kaliappan M.,Vimal S.,Annamalai Suresh

Publisher

Springer Science and Business Media LLC

Subject

Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1007/s10916-019-1402-6.pdf

Reference37 articles.

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3. El-Moselhy, E. A., Borg, H. M., and Atlam, S. A., Cervical cancer: Sociode-mographic and clinical risk factors among adult Egyptian females. J. Oncol. Res. Treat. 1(1):7, 2016.

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5. Vimal, S., Kalaivani, L., and Kaliappan, M., Collaborative approach on mitigating spectrum sensing data hijack attack and dynamic spectrum allocation based on CASG modeling in wireless cognitive radio networks. Cluster Computing, 2017. https://doi.org/10.1007/s10586-017-1092-0 .

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