Electromagnetic Fields Literature Analysis for Precision Medicine.
This paper describes a literature-mining analysis of more than 30,000 EMF-related publications to extract genes, diseases, and molecular mechanisms linked to EMF exposure across six EMF subsets. The authors report identifying 3,653 unique disease MeSH terms and 9,966 unique genes, including 4,340 human genes. The work is presented as a way to highlight molecular aspects of increasing EMF exposure rather than as a direct test of health effects.
Key points
- The study uses text mining of EMF-related publications rather than collecting new exposure or health outcome data.
- It reports extracting gene, disease, and molecular mechanism associations related to EMF exposure across six EMF subsets.
- A total of 3,653 unique disease MeSH terms were identified from the mined literature.
- A total of 9,966 unique genes were identified, with 4,340 reported as human genes.
- The abstract frames the work as supporting molecular-level understanding relevant to increasing EMF exposures.
- The abstract does not report effect sizes, risk estimates, or causal conclusions about EMF health impacts.
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AI-generated summaries may be incomplete or incorrect. This content is for informational purposes only and is not medical advice.
AI-generated summaries may be incomplete or incorrect. This content is for informational purposes only and is not medical advice.
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