Effects of radiofrequency electromagnetic fields (RF EMF) on cancer in laboratory animal studies: A protocol for a systematic review

Mevissen, Meike; Ward, Jerrold M.; Kopp‐Schneider, Annette; McNamee, James P.; Wood, Andrew W.; Rivero, Tania M; Thayer, Kristina A.; Straif, Kurt

doi:10.1016/j.envint.2022.107106

Cited by 11 publications

(9 citation statements)

References 28 publications

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“…There are ten SRs, the one on surveying and ranking of health effects, which are involved in those of the other nine SRs. Of these, four involving AS [115][116][117][118], three regarding cancers and oxidative stress [119][120][121], two on male fertility and pregnancy outcomes [122,123]. The following points summarize these categories.…”

Section: Case Of Who Assessmentsmentioning

confidence: 99%

“…Recently, the WHO has supported research and managed a special issue involving SRs on health effects of exposure to RF-EMF: WHO assessment of health effects of exposure to radiofrequency electromagnetic fields: systematic reviews, 2022, [114][115][116][117][118][119][120][121][122][123]. The WHO had a project to assess prospective health effects of exposure to RF-EMF in the broad and working population.…”

Section: Case Of Who Assessmentsmentioning

confidence: 99%

“…SR on Cancers and Oxidative Stress [119][120][121] The first SR [119] aimed to assess the literature regarding the possibility that RF fields can induce cellular oxidative stress. Such stress is accompanied by an amplified creation of oxidizing species or a substantial decrease in the ability of antioxidant defenses.…”

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confidence: 99%

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Assessment and Categorization of Biological Effects and Atypical Symptoms Owing to Exposure to RF Fields from Wireless Energy Devices

Razek

2023

Applied Sciences

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Nowadays, environmental electromagnetic fields exist everywhere and the whole population is exposed. The most widespread technologies engendering exposure to electromagnetic fields for the public and workers are radiofrequency wireless communication systems. Such exposure can have direct effects on living tissue involving biological problems or personal symptoms, as well as indirect effects restricting healthcare appliances. This assessment aims to analyze, examine and categorize the consequences of non-ionizing electromagnetic fields emitted by radiofrequency devices. This concerns biological effects in living tissues and atypical personal symptoms for short and long-term exposures. The evaluation methodology in this field of investigation is also discussed. In the article, these consequences as well as their evaluation techniques, in the case of wireless digital communication tools, are analyzed and reviewed. The categorization of exposure sources, the corresponding effects and their assessment methodologies are analyzed. The concept of systematic reviews and meta-analyses and their applications in various assessments of these effects and symptoms are reviewed and discussed.

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Section: Case Of Who Assessmentsmentioning

confidence: 99%

Section: Case Of Who Assessmentsmentioning

confidence: 99%

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Assessment and Categorization of Biological Effects and Atypical Symptoms Owing to Exposure to RF Fields from Wireless Energy Devices

Razek

2023

Applied Sciences

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“…Niestety bezpo rednie zastosowanie tego formalizmu jest bardzo trudnym i nierozwi zywalnym zagadnieniem wielu ciał. Zdolno ci modyfikacji systemów przez pola elektromagnetyczne s przedmiotem wielu bada [8]. Obecnie wiele chorób, w ró nych dziedzinach medycyny, leczonych jest za pomoc niejonizuj cej energii elektromagnetycznej, chocia mechanizm działania nie jest w pełni wyja niony.…”

Section: Wst Punclassified

Dystrybucja Pola Elekrtomagnetycznego Po Przejściu Przez Ciała Stała. Analiza Porównawcza

KŁOS-WITKOWSKA¹,

KRZYSTECZKO²,

MARTSENYUK³

2022

Projektowanie, Badania I Eksploatacja

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The aim of the study was to investigate the distribution of the electromagnetic field after passage through: silicon, iron , zinc. The experiment was performed for 0,1; 5; 10; 50; 100; 150; 170; 190; 200; 230; 250 MHz. Analysis of the scans showed changes in field parameters as a function of frequency and substance. The effect was explained using the mechanisms of electromagnetic field interaction with matter.

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“…frequency (RF) electromagnetic field (EMF) [4]. Phased arrays are typically limited by radio frequency (RF) electromagnetic field (EMF) exposure rules.…”

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confidence: 99%

Machine Learning Modeling for Radiofrequency Electromagnetic Fields (RF-EMF) Signals From mmWave 5G Signals

et al. 2023

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The authors would like to acknowledge IGNITE -Interference Modeling for 5G and FSS Coexistence at mmWave with Climate Change Considerations in the Tropical Region (FRGS/1/2021/TK0/UPM/01/1) and BIDANET: Parametric Big Data Analytics over Wireless Networks (UPM.RMC.800-3/3/1/GPB/2021/9696300, Vot No.: 9696300) for the financial assistance in the measurement campaign. This project is a collaboration with Rohde & Schwarz Malaysia for consultations on the measurement analysis.ABSTRACT 5G is the next-generation mobile communication technology expected to deliver more excellent data rates than Long Term Evolution (LTE). It offers ultra-low latency and ultra-high dependability, allowing revolutionary services across sectors. 5G mm-Wave base stations may emit harmful radiofrequency electromagnetic fields (RF-EMF). However, RF-EMF concern raises health and safety. From our research, the RF-EMF prediction model lacks papers or publications. This study uses IEEE and ICNIRP standards for assessment and exposure limits. The measuring campaign analyses one sector of a 5G base station (5G-BS) operation on 29.5 GHz in Cyberjaya, Malaysia. This study proposes two prediction models. The first model predicts signal beam RF-EMF, and the second predicts base station RF-EMF. Each model contains three neural network techniques to forecast RF-EMF values: Approximate-RBFNN, Exact-RBFNN, and GRNN. The results are analysed and compared with the measured data, observing which algorithm is more accurate by calculating the RMSE of each algorithm. As a result, it can observe that the Exact-RBFNN algorithm is the best algorithm to predict the RF-EMF because it shows a good agreement with the measured value. Besides that, in 1-min duration, the difference between predicted and measured values reached 0.2 less channels. However, in 6-min and 30-min, it can observe more accurate results since the differences between values reached 0.1in the situations. In addition, the ICNIRP standard was used and compared with the result and validation value of the algorithms.

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Effects of radiofrequency electromagnetic fields (RF EMF) on cancer in laboratory animal studies: A protocol for a systematic review

Cited by 11 publications

References 28 publications

Assessment and Categorization of Biological Effects and Atypical Symptoms Owing to Exposure to RF Fields from Wireless Energy Devices

Assessment and Categorization of Biological Effects and Atypical Symptoms Owing to Exposure to RF Fields from Wireless Energy Devices

Dystrybucja Pola Elekrtomagnetycznego Po Przejściu Przez Ciała Stała. Analiza Porównawcza

Machine Learning Modeling for Radiofrequency Electromagnetic Fields (RF-EMF) Signals From mmWave 5G Signals

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