Authors
Md Mehrab Shahriar, Mirza Shaheen Iqubal, Samrat Mitra, Amit Kumar Das
Publication date
2019/7/1
Conference
2019 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)
Pages
145-149
Publisher
IEEE
Description
The state of malnutrition can be considered as a predominant issue for a developing nation like Bangladesh. Since today's children are the future's workforce, it explicitly impacts to the economic improvement of Bangladesh. So, prevention of child malnutrition is the most foremost investigation at this stage. The study aims to classify malnutrition based on deep learning approach of predictive modeling on significant malnutrition features to predict malnutrition status of a 0-59 months' older child. To do so an Artificial Neural Network (ANN) approach is applied to Bangladesh Demographic and Health Survey 2014 (BDHS) children data. This study clarifies how a predictive model classifies the malnutrition condition. ANN approach shows the best accuracy with wasting, underweight, and stunting. In conclusion, determining the malnutrition status using deep learning approach is the most scientific way to deal with it both …
Total citations
20202021202220232024461088
Scholar articles
MM Shahriar, MS Iqubal, S Mitra, AK Das - 2019 IEEE International Conference on Industry 4.0 …, 2019