The paper describes a novel approach based on Machine Learning (ML) to characterize the exposure of children to extremely low frequency magnetic field (ELF-MF, 40-800Hz). Unsupervised cluster analysis is applied on MF registrations from a cohort 977 children during 24h. The aim is to better characterize children exposure with respect to daily activities, subject location, environmental conditions.
Modelling and Characterization of ELF MF Exposure of Children with Machine Learning Techniques
Gabriella Tognola;Marta Bonato;Emma Chiaramello;Serena Fiocchi;Marta Parazzini;
2018
Abstract
The paper describes a novel approach based on Machine Learning (ML) to characterize the exposure of children to extremely low frequency magnetic field (ELF-MF, 40-800Hz). Unsupervised cluster analysis is applied on MF registrations from a cohort 977 children during 24h. The aim is to better characterize children exposure with respect to daily activities, subject location, environmental conditions.File in questo prodotto:
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