Iranian Study: Machine Learning Predicts Health Symptoms Near Cell Towers with 85% Accuracy โ€” EMF Signal
๐Ÿ‡ณ๐Ÿ‡ด Norsk
โ† EMF Signal Journal of Biomedical Physics and Engineering
Research

๐Ÿ‡ฎ๐Ÿ‡ท Iranian Study: Machine Learning Predicts Health Symptoms Near Cell Towers with 85% Accuracy

Feb 17, 2026 (EMFS)
Feb 1, 2026 (original)

Researchers from Iran developed an AI-based decision support system that can predict health symptoms like headaches, sleep disturbance, and dizziness in people living near mobile phone base stations, achieving up to 85% accuracy.

"The rapid increase in the number of Mobile Phone Base Stations has raised global concerns about the potential adverse health effects of exposure to Radiofrequency Electromagnetic Fields."

โ€” Parsaei et al.

"The SVM-based model demonstrated strong performance, with accuracies of 85.3%, 82%, 84%, 82.4%, and 65.1% for headache, sleep disturbance, dizziness, vertigo, and fatigue, respectively."

โ€” Study Results

Source

A Decision Support System for Managing Health Symptoms of Living Near Mobile Phone Base Stations pubmed.ncbi.nlm.nih.gov
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