Inferences, Risk Modeling, and Prediction of Health Effects of Ionizing Radiation
| Autor: | Nicholas Dainiak |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Internationality Epidemiology Adverse outcomes Health Toxicology and Mutagenesis Experimental laboratory Models Biological Risk Assessment Ionizing radiation 03 medical and health sciences 0302 clinical medicine Radiation Ionizing Medicine Low dose ct Computer Simulation Radiology Nuclear Medicine and imaging Radiation Injuries Radiometry business.industry Incidence Medical practice Dose-Response Relationship Radiation Radiation Exposure 030104 developmental biology Threshold dose Risk analysis (engineering) 030220 oncology & carcinogenesis Maximum Allowable Concentration Radiation protection business Risk assessment |
| Zdroj: | Health Physics. 110:271-273 |
| ISSN: | 0017-9078 |
| DOI: | 10.1097/hp.0000000000000465 |
| Popis: | The combined expertise of radiation epidemiologists and laboratory experimentalists is required to accurately define health risks from exposure to a low/very low radiation dose. Although stochastic risk can be estimated when a known threshold dose is exceeded, risk must be inferred from data transference at sub-threshold doses. The clinician's dilemma is evident when complying with accepted medical practice that is complicated by potential long-term, adverse outcomes. By contrast, radiation protection regulators must make prudent judgments without complete knowledge of the scope and consequences of their actions. Only by combining the strengths of epidemiological and experimental laboratory approaches can accurate predictive modeling be achieved after exposure to a low/very low dose. |
| Databáze: | OpenAIRE |
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