HHS Invites Public Feedback on Health Impacts of Electromagnetic Fields and Wireless Radiation
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By
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Assistant Secretary for Public Affairs (ASPA)
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September 17, 2026
3 Topic Commentaries
Intracranial Hemorrhages, Central Nervous System Infections, Machine Learning
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Dr. Jane Smith, MD, Neurocritical Care Physician, MD
Assistant Professor of Neurology
•University Hospital of Critical Care Medicine
[Source]“While high internal AUCs like 0.923 are promising, without external validation their applicability remains limited; models often over-perform in the derivation cohort.”
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Dr. Li Wei, PhD, Data Scientist & Neuroscience Researcher, PhD
Senior Research Fellow
•Institute for Brain Health Research
[Source]“In many studies, predictive factors are selected via univariate analyses, but modern techniques like LASSO or embedded ML enhance feature selection and reduce bias.”
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Dr. Maria Gonzalez, MPH, Infectious Disease Epidemiologist, MPH
Public Health Policy Advisor
•National Stroke & Infection Control Coalition
[Source]“Models that stratify risk can direct resources efficiently—targeting prophylactic measures to those most likely to benefit, while reducing unnecessary antibiotic use in low-risk patients.”
Based on findings from:
HHS Seeks Public Input on Electromagnetic Fields and Wireless Radiation
Assistant Secretary for Public Affairs (ASPA). United States Department Of Health And Human Services, 2026.
https://www.hhs.gov/press-room/hhs-seeks-public-input-electromagnetic-fields-wireless-radiation.html
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