Neural Network and Fractal Analysis of Multiscale Electromagnetic Field Interaction in the Male Urogenital System

The detrimental influence of Wi-Fi and mobile phones on human health has been extensively studied, yet the multiscale spatial complexity of electromagnetic energy absorption in biological tissues is still poorly understood. This paper offers a computational investigation of radiofrequency electromagnetic field (RF-EMF) exposure in the male urogenital system using fractals and neural networks. The specific absorption rate (SAR) produced by a 2.4 GHz antenna positioned in anatomically important locations is calculated using a realistic voxel-based anatomical model (GUSTAV) implemented in CST Microwave Studio. Fractal geometry is used to statistically examine the spatial distribution of absorbed electromagnetic radiation beyond traditional SAR evaluation, revealing scale-dependent variability linked to anatomical complexity. To describe multiscale energy localization in prostate, testicular, and penile tissues, fractal dimension metrics are taken from SAR maps. The nonlinear link between antenna position and fractal-informed SAR distributions is then modeled by a feedforward neural network. The findings show that SAR patterns clearly display fractal behavior, with higher fractal dimensions indicating more localized energy concentration and tissue heterogeneity. These results demonstrate a strong connection between fractal complexity, anatomical multiscale structure, and electromagnetic exposure, placing the suggested framework firmly within the field of fractal modeling of biomedical systems.