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Deep Learning Features in Atmospheric Chemistry: Prediction of Cancer Morbidity Due to Air Pollution

Authors :
Mitchell Thayer
Amir H. Assadi
Kaixi Zhu
Fenghua Yu
Ehsan Qasemi
Source :
2017 International Conference on Computational Science and Computational Intelligence (CSCI).
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

Atmospheric Chemistry is important in public health. This paper highlights methodology aspects from analysis of atmospheric chemistry data in China, its correlation with cancer morbidity data, and impact on future cancer morbidity rate that are due to changes in climate.Forthcoming papers use DL for prediction. Research on cancer and analysis of cancer morbidity are provided by Liu Yuxin, Zhaorong Zhu [5].

Details

Database :
OpenAIRE
Journal :
2017 International Conference on Computational Science and Computational Intelligence (CSCI)
Accession number :
edsair.doi...........a094af301e6bd48c84282967ec602c98
Full Text :
https://doi.org/10.1109/csci.2017.307