This analytical study evaluated machine learning models (SVM and Random Forest) to predict health symptoms in adults living near mobile phone base stations. The SVM model reportedly achieved high predictive performance for headache, sleep disturbance, dizziness, vertigo, and fatigue, and outperformed Random Forest and prior models. The abstract concludes that proximity to base stations is connected with increased prevalence of several symptoms and emphasizes distance, age, and duration of residence as key predictors.