Artificial neural network based prediction of malaria abundances using big data: A knowledge capturing approach Thakur Santosh , Dharavath Ramesh Clinical.

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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 121-126 (March 2019) DOI: 10.1016/j.cegh.2018.03.001 Copyright © 2018 INDIACLEN Terms and Conditions

Fig. 1 Map of India showing areas in Khammam District, selected for study. Clinical Epidemiology and Global Health 2019 7, 121-126DOI: (10.1016/j.cegh.2018.03.001) Copyright © 2018 INDIACLEN Terms and Conditions

Fig. 2 Visualisation of feed forward neural networks. Clinical Epidemiology and Global Health 2019 7, 121-126DOI: (10.1016/j.cegh.2018.03.001) Copyright © 2018 INDIACLEN Terms and Conditions

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, 121-126DOI: (10.1016/j.cegh.2018.03.001) Copyright © 2018 INDIACLEN Terms and Conditions

Fig. 4 Predicted vs Observed malaria cases from Jan 2015 to 31 Dec 2015. Clinical Epidemiology and Global Health 2019 7, 121-126DOI: (10.1016/j.cegh.2018.03.001) Copyright © 2018 INDIACLEN Terms and Conditions