alexa Application of Data Mining Techniques to Predict Adult
ISSN: 2157-7420

Journal of Health & Medical Informatics
Open Access

Like us on:
OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Application of Data Mining Techniques to Predict Adult Mortality: The Case of Butajira Rural Health Program, Butajira, Ethiopia

Tesfahun Hailemariam1*, Million Meshesha2 and Alemayehu Worku3

1Department of Health Informatics, Hawassa Health Science College, Hawassa, Ethiopia

2Department of Information Science, School of Information Science, Addis Ababa University, Addis Ababa, Ethiopia

3School of Community Health Department, Addis Ababa University, Addis Ababa, Ethiopia

*Corresponding Author:
Tesfahun Hailemariam
Department of Health Informatics
Hawassa Health Science College
Hawassa, Ethiopia
Tel: +251934107979
E-mail: tesfahunhailemariam

Received date: May 27, 2015 Accepted date: July 24, 2015 Published date: July 31, 2015

Citation: Hailemariam T, Meshesha M, Worku A (2015) Application of Data Mining Techniques to Predict Adult Mortality: The Case of Butajira Rural Health Program,Butajira, Ethiopia. J Health Med Informat 6:197. doi: 10.4172/2157-7420.1000197

Copyright: © 2015 Hailemariam T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.



Background: Though adults are care providers and risk takers of a society, reports indicate that adult mortality conditions are not given much emphasis. This is due to a widespread perception that mortality among adults is low. Every year, more than 7•7 million children die before their fifth birthday; however, nearly 24 million of adults die under the age of 70 years. Identifying major determinants for adult death helps to alleviate the loss of the productive group. Therefore, this research is aimed to apply data mining techniques to build a model that can assist in predicting adult health status.
Methods: The hybrid model that was developed for academic research was followed. Dataset was preprocessed for data transformation, missing values and outliers. WEKA 3.6.8 data mining tools and techniques such as J48 decision tree and Naïve Bayes algorithms were employed to build the predictive model by using a sample dataset of 62,869 instances of both alive and died adults through three experiments and six scenarios. The area under the ROC curve for outcome class is used to evaluate performances of models from the predictive algorithms.
Results: In this study as compared to Bayes, the performance of J48 pruned decision tree reveals that 97.2% of accurate results are possible for developing classification rules that can be used for prediction. If no education in family and the person is living in rural highland and lowland, the probability of experiencing adult death is 98.4% and 97.4% respectively with concomitant attributes in the rule generated. The likely chance of adult to survive in completed primary school, completed secondary school, and further education is (98.9%, 99%, 100%) respectively.
Conclusion: Predictive model built with the use of data mining techniques suggests that education plays a considerable role as a root cause of adult death, followed by outmigration. The possibility of incorporating the findings of this study with knowledge based system should be explored so that experts can consult the system in their problem solving and decision making process. Further comprehensive and extensive experimentation is needed to substantially describe the loss experience of adult mortality in Ethiopia.


Share This Page

Additional Info

Loading Please wait..
Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri, Food, Aqua and Veterinary Science Journals

Dr. Krish

[email protected]

1-702-714-7001 Extn: 9040

Clinical and Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals


[email protected]

1-702-714-7001Extn: 9042

Chemical Engineering and Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001 Extn: 9040

Earth & Environmental Sciences

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

General Science and Health care Journals

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics and Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001 Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Informatics Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Material Sciences Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Mathematics and Physics Journals

Jim Willison

[email protected]

1-702-714-7001 Extn: 9042

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001 Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

John Behannon

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001 Extn: 9042

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version