A Multilayer Perceptron Neural Network–Based Model for Predicting Subjective Health Symptoms in People Living in the Vicinity of Mobile Phone Base Stations H. Parsaei, 1 M. Faraz, 1 and S. M. J. Mortazavi 2,3 1 Medical Physics and Medical Engineering Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran. 2 Department of Diagnostic Imaging, Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA. 3 Ionizing and Non-ionizing Radiation Protection Research Center (INIRPRC), Shiraz University of Medical Sciences, Shiraz, Iran. Abstract Advances in modern technologies such as telecommunication have widely expanded the applications of wireless systems. Therefore, humans are continuously exposed to electromagnetic fields (EMFs) produced by widely used devices such as mobile and cordless phones and Wi-Fi routers. According to the World Health Organization, electromagnetic hypersensitivity (EHS) is the medical term for a variety of nonspecific symptoms that afflicted subjects attribute to exposure to different sources of EMFs. About 25% of the general population reports different levels of environmental intolerance to factors such as EMFs, and studies performed in Europe show that about 75% of general practitioners had visited patients com- plaining of EHS. In this paper, multilayer perceptron neural network (MLPNN)–based models are proposed to predict the subjective health symptoms in inhabitants living in the vicinity of mobile phone base stations. The classifier uses several parameters such as demographic data, environmental exposure to a mobile phone station, and the health conditions of an individual as input to estimate subjective health symptoms. Out of 699 data sets recorded from 363 men and 336 women via questionnaire, 70% were used for training, 15% for validation, and the remaining 15% for testing the developed system. The performance of the developed system (sensitivity and specificity) in predicting the subjective health symptoms is as follows: headache (72%, 91%), fatigue (8%, 98%), sleep disturbance (97%, 93%), dizziness (65%, 85%), vertigo (65%, 84%). These promising re- sults suggest that this system might be useful as a means for pre- dicting the health symptoms in people living in the vicinity of mobile phone base stations, which ultimately enhances the quality of life of these individuals through providing appropriate medi- cal care and introducing effective methods for reducing the effect of these exposures. Key Words: Mobile phone base stations— Electromagnetic hypersensitivity (EHS)—Artificial neural network— Radiofrequency. 1. Introduction T he past few decades have witnessed an exponential advance in modern technologies such as telecommunication and the applications of wireless systems. More than ever, now hu- mans are continuously exposed to electromagnetic fields (EMFs) produced by different sources ranging from wireless baby monitors to Wi-Fi routers and mobile and cordless phones. The rapid growth of wireless technology has raised global concerns about how exposure to EMFs may affect human health (Abdel-Rassoul et al., 2007; Berg-Beckhoff et al., 2009; Bortkiewicz et al., 2012; Gomes DOI: 10.1089/eco.2017.0011 ª MARY ANN LIEBERT, INC.  VOL. 9 NO. 2  JUNE 2017 ECOPSYCHOLOGY 99 Downloaded by 197.88.125.14 from online.liebertpub.com at 08/27/17. For personal use only.