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[Poster] Association between prenatal exposure to ambient p..:

, In: ACM SIGCAS Conference on Computing and Sustainable Societies,

Ogawa Kawano, Ayako - p. 402-408 , 2021

Link: https://dl.acm.org/doi/10.1145/3460112.3472312

RT 
T1 <cTitle>ACM SIGCAS Conference on Computing and Sustainable Societies</cTitle>: T1 <Title>[Poster] Association between prenatal exposure to ambient particulate matter (PM2.5) and adverse birth outcomes in Nepal and Bangladesh using the prediction model for daily PM2.5 concentrations matched with demographic and health survey data: spatio-temporal analysis				: Predicting PM2.5 in Nepal and Bangladesh using XGBoost, LightGBM, and deep learning with multisource satellite data including Sentinel-5P</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3472312&Exemplar=1&LAN=DE
				
A1 Ogawa Kawano, Ayako
PB ACM
YR 2021
K1 Ambient air pollution
K1 Deep learning
K1 Developmental Origins of Health and Disease
K1 Fine particulate matter
K1 Global health
K1 Low birth weight
K1 Predictive modeling
K1 Preterm birth
K1 Supervised machine learning
K1 Computing methodologies
K1 Machine learning
K1 Applied computing
K1 Physical sciences and engineering
K1 Earth and atmospheric sciences
SP 402
OP 408
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3460112.3472312
DO https://dl.acm.org/doi/10.1145/3460112.3472312
SF ELIB - SuUB Bremen

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