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Paper Abstract and Keywords
Presentation 2017-12-02 15:15
Using Biological Variables and Social Determinants to Predict Malaria and Anaemia among Children in Senegal
Boubacar Sow, Hiroki Suguri (Miyagi Univ.), Hamid Mukhtar (Taif Univ.), Hafiz Farooq Ahmad (KFU) SWIM2017-21
Abstract (in Japanese) (See Japanese page) 
(in English) Integrating machine learning techniques in healthcare has become very common nowadays, and has contributed positively to improving clinical care and health decisions planning. Anemia and malaria are two life-threating diseases in Africa which affect the red blood cells and reduce hemoglobin production. This paper focuses on analyzing health data using four machine learning algorithms: KNN, Random Forests, SVM and Naïve Bayes. Our task aims to investigate data collected in Senegal by the Demographic and Health Survey (DHS) and to find out hidden information for anemia and malaria. We present two classification models for the two blood disorders using biological variables and social determinants of health. The findings of this research will contribute to improving child healthcare in Senegal by eradicating anemia and malaria, and decreasing child mortality rate.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Anemia / Malaria / Biological Variables / Social Determinants / Children health / DHS /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 336, SWIM2017-21, pp. 13-20, Dec. 2017.
Paper # SWIM2017-21 
Date of Issue 2017-11-25 (SWIM) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SWIM2017-21

Conference Information
Committee SWIM  
Conference Date 2017-12-02 - 2017-12-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Tokyo University of Science, Kagurazaka Campus, Fujimi Building 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Implementation of Modeling, General (Workshop) 
Paper Information
Registration To SWIM 
Conference Code 2017-12-SWIM 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Using Biological Variables and Social Determinants to Predict Malaria and Anaemia among Children in Senegal 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Anemia  
Keyword(3) Malaria  
Keyword(4) Biological Variables  
Keyword(5) Social Determinants  
Keyword(6) Children health  
Keyword(7) DHS  
Keyword(8)  
1st Author's Name Boubacar Sow  
1st Author's Affiliation Miyagi University (Miyagi Univ.)
2nd Author's Name Hiroki Suguri  
2nd Author's Affiliation Miyagi University (Miyagi Univ.)
3rd Author's Name Hamid Mukhtar  
3rd Author's Affiliation Taif University (Taif Univ.)
4th Author's Name Hafiz Farooq Ahmad  
4th Author's Affiliation King Faisal University (KFU)
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Speaker Author-1 
Date Time 2017-12-02 15:15:00 
Presentation Time 30 minutes 
Registration for SWIM 
Paper # SWIM2017-21 
Volume (vol) vol.117 
Number (no) no.336 
Page pp.13-20 
#Pages 8 
Date of Issue 2017-11-25 (SWIM) 

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