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Classification of Maternal Healthcare Data using Naïve Bayes

P. Kour1 , S. Shastri2 , A.S. Bhadwal3 , S. Kumar4 , K. Singh5 , M. Kumari6 , A. Sharma7 , V. Mansotra8

Section:Review Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 388-394, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.388394

Online published on Mar 31, 2019

Copyright © P. Kour, S. Shastri, A.S. Bhadwal, S. Kumar, K. Singh, M. Kumari, A. Sharma, V. Mansotra . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: P. Kour, S. Shastri, A.S. Bhadwal, S. Kumar, K. Singh, M. Kumari, A. Sharma, V. Mansotra, “Classification of Maternal Healthcare Data using Naïve Bayes,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.388-394, 2019.

MLA Style Citation: P. Kour, S. Shastri, A.S. Bhadwal, S. Kumar, K. Singh, M. Kumari, A. Sharma, V. Mansotra "Classification of Maternal Healthcare Data using Naïve Bayes." International Journal of Computer Sciences and Engineering 7.3 (2019): 388-394.

APA Style Citation: P. Kour, S. Shastri, A.S. Bhadwal, S. Kumar, K. Singh, M. Kumari, A. Sharma, V. Mansotra, (2019). Classification of Maternal Healthcare Data using Naïve Bayes. International Journal of Computer Sciences and Engineering, 7(3), 388-394.

BibTex Style Citation:
@article{Kour_2019,
author = {P. Kour, S. Shastri, A.S. Bhadwal, S. Kumar, K. Singh, M. Kumari, A. Sharma, V. Mansotra},
title = {Classification of Maternal Healthcare Data using Naïve Bayes},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {388-394},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3850},
doi = {https://doi.org/10.26438/ijcse/v7i3.388394}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.388394}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3850
TI - Classification of Maternal Healthcare Data using Naïve Bayes
T2 - International Journal of Computer Sciences and Engineering
AU - P. Kour, S. Shastri, A.S. Bhadwal, S. Kumar, K. Singh, M. Kumari, A. Sharma, V. Mansotra
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 388-394
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Data Mining and Machine Learning are the emerging research fields that are gaining popularity in many areas including healthcare, education, spam filtering, manufacturing, CRM, fraud detection, intrusion detection, financial banking, customer segmentation, research analysis and many others due to their infinite applications and methodologies to discover the trends and knowledge from voluminous databases in the novel manner. Healthcare industry produces gigantic amount of data related to child immunization, maternal health, family planning, clinical data, health surveys, diagnosis etc. As the process of data collection in health sector increases, the usage of data mining and machine learning techniques for analyzing and decision making also increases. There is one major health issue in health sector i.e. maternal health that needs to be worried about. In this research paper, the maternal health data of the state of Jammu and Kashmir, India has been collected from HMIS portal and Naive Bayes classification algorithm of data mining has been used for the analysis. Various performance measures including Accuracy, Precision, Recall, Kappa, F-measure, AUC and Gini have also been used for calculating the performance.

Key-Words / Index Term

Data Mining, Machine Learning, Maternal Health, Naïve Bayes

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