Publication Type:

Conference Paper

Source:

Procedia Computer Science, Elsevier B.V., Volume 115, p.338-349 (2017)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032455260&doi=10.1016%2fj.procs.2017.09.087&partnerID=40&md5=d4a32f4e460386b0662170ecea8a97a8

Keywords:

Artificial intelligence, Developing countries, IDHS dataset India, Information Gain, Learning systems, Logistic regressions, malnutrition, nutrition, Nutritional Status, Population statistics, Regression analysis, Surveys

Abstract:

<p>Malnutrition is the leading causes of infant mortality among the developing countries including India. This study designs a prediction model for malnutrition based on machine learning approach, using the available features in the Indian Demographic and Health Survey (IDHS) dataset and comparing that with the literature identified features. Our findings suggest that machine learning approach identifies some important features not identified in extant literature. Subsequently, logistic regression was carried out to identify the probabilities of these features in explaining malnutrition. The paper contributes in exploring the possibilities of using artificial intelligence in identifying probable correlates of malnutrition. © 2017 The Author(s).</p>

Notes:

cited By 0; Conference of 7th International Conference on Advances in Computing and Communications, ICACC 2017 ; Conference Date: 22 August 2017 Through 24 August 2017; Conference Code:131212

Cite this Research Publication

S. Khare, Kavyashree, S., Gupta, D., and Jyotishi, A., “Investigation of Nutritional Status of Children based on Machine Learning Techniques using Indian Demographic and Health Survey Data”, in Procedia Computer Science, 2017, vol. 115, pp. 338-349.

207
PROGRAMS
OFFERED
6
AMRITA
CAMPUSES
15
CONSTITUENT
SCHOOLS
A
GRADE BY
NAAC, MHRD
8th
RANK(INDIA):
NIRF 2018
150+
INTERNATIONAL
PARTNERS