A Decision Support System for Managing Health Symptoms of Living Near Mobile Phone Base Stations
Research
RF Safe Research Library
Jan 1, 2024
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…
Supervised Machine Learning Algorithms for Bioelectromagnetics: Prediction Models and Feature Selection Techniques Using Data from Weak Radiofrequency Radiation Effect on Human and Animals Cells.
Research
RF Safe Research Library
Jan 1, 2020
This paper develops supervised machine-learning prediction models to analyze potential impacts of weak RF-EMF on human and animal cells using extracted laboratory experimental data from prior publications. Data from 300 peer-reviewed papers (1127 experimental case studies) were used with feature selection and…