1. Artificial neural network based prediction of malaria abundances using big data: A knowledge capturing approach 
Thakur Santosh , Dharavath Ramesh  
Clinical Epidemiology and Global Health 
Volume 7, Issue 1, Pages (March 2019)
DOI: /j.cegh
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2. Fig. 1
Map of India showing areas in Khammam District, selected for study.
Clinical Epidemiology and Global Health 2019 7, DOI: ( /j.cegh )
Copyright © 2018 INDIACLEN Terms and Conditions

3. Fig. 2 Visualisation of feed forward neural networks.
Clinical Epidemiology and Global Health 2019 7, DOI: ( /j.cegh )
Copyright © 2018 INDIACLEN Terms and Conditions

4. Fig. 3
(a) Predicted and observed malaria instances for Aswaraopeta Area. (b) Predicted and observed malaria instances for Venkatapuram Area. (c) Predicted and observed malaria instances for Khammam Area. (d) Predicted and observed malaria instances for Aswapuram Area. Predicted and observed instances for all geographical areas.
Clinical Epidemiology and Global Health 2019 7, DOI: ( /j.cegh )
Copyright © 2018 INDIACLEN Terms and Conditions

5. Fig. 4
Predicted vs Observed malaria cases from Jan 2015 to 31 Dec 2015.
Clinical Epidemiology and Global Health 2019 7, DOI: ( /j.cegh )
Copyright © 2018 INDIACLEN Terms and Conditions