2026 EMF Research Snapshot: Non‑Thermal Biological Effects Across 6 GHz, 3.5 GHz, 2.45 GHz Wi‑Fi, and 28 GHz mmWave—Why Thermal‑Only Safety Limits Are Not Enough
Research
Effect Synthesis
Mar 1, 2026
Synthesis of 12 studies (2026) linking RF/EMF exposures and wireless tech use to oxidative stress, apoptosis, reproductive harm, kidney changes, sleep disruption, and base-station symptom patterns—supporting precautio…
Prediction of smartphone overdependence and analysis of its influencing factors among older adults based on machine learning.
Research
RF Safe Research Library
Jan 1, 2026
This study used panel data from South Korea's 2023 Smartphone Overdependence Survey to build and compare machine-learning models predicting smartphone overdependence among adults aged 60+. Among evaluated classifiers, XGBoost had the best reported predictive performance (accuracy 0.925). The most important predictors…
Machine Learning Approach for Ground-Level Estimation of Electromagnetic Radiation in the Near Field of 5G Base Stations
Research
RF Safe Research Library
Jan 1, 2025
This paper presents a machine-learning method to estimate ground-level electromagnetic radiation (electric field strength) in the near field of 5G base stations, using multiple technical and environmental input parameters. The authors report experimental performance with a mean absolute percentage error of about…
Evaluation of Personal Radiation Exposure from Wireless Signals in Indoor and Outdoor Environments
Research
RF Safe Research Library
Jan 1, 2025
This exposure assessment measured personal RF electric field strength in multiple indoor and outdoor micro-environments in Malaysia using an ExpoM-RF 4 meter and modeled exposure with machine learning (FCNN, XG Boost) and linear regression. Reported exposures were usually below the stated public limit (61.4 V/m), but…
Analyzing the Impact of Occupational Exposures on Male Fertility Indicators: A Machine Learning Approach
Research
RF Safe Research Library
Jan 1, 2025
This occupational epidemiology study used machine learning to evaluate whether workplace exposures (including magnetic and electric fields, vibration, noise, and heat stress) predict male reproductive indicators in 80 workers. The models and explainable AI outputs highlighted magnetic and electric field exposures and…
In-Depth Analysis of Chlorophyll Fluorescence Rise Kinetics Reveals Interference Effects of a Radiofrequency Electromagnetic Field (RF-EMF) on Plant Hormetic Responses to Drought Stress.
Research
RF Safe Research Library
Jan 1, 2025
This experimental study assessed chlorophyll fluorescence rise kinetics in lettuce plants exposed to RF-EMFs and subjected to a short drought treatment. Using a conventional JIP test and a machine learning-assisted anomaly-detection approach, the authors report that RF-EMF exposure weakened drought-induced hormetic…
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…