Ehsan Qasemi
Deep Learning Features in Atmospheric Chemistry
Highlights:
- -> Big data local-to-global methods in analysis and prediction of dynamics in atmospheric chemistry spatiotemporal data.
Publications:
- Yu F, Thayer M, Qasemi E, Zhu K, Assadi A. Deep Learning Features in Atmospheric Chemistry: Prediction of Cancer Morbidity Due to Air Pollution. In2017 International Conference on Computational Science and Computational Intelligence (CSCI) 2017 Dec 14 (pp. 1764-1766). IEEE.
Details:
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.
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