| Inference and uncertainty in radiology. | |
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MedLine Citation:
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PMID: 16627199 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This paper seeks to enhance understanding of the philosophical underpinnings of our discipline and the resulting practical implications. Radiology reports exist in order to convey new knowledge about a patient's condition based on empiric observations from anatomic or functional images of the body. The route to explanation and prediction from empiric evidence is mostly through inference based on inductive (and sometimes abductive) arguments. The conclusions of inductive arguments are, by definition, contingent and provisional. Therefore, it is necessary to deal in some way with the uncertainty of inferential conclusions (i.e. interpretations) made in radiology reports. Two paradigms for managing uncertainty in natural sciences exist in dialectic tension with each other. These are the frequentist and Bayesian theories of probability. Tension between them is mirrored during routine interactions among radiologists and clinicians. I will describe these core issues and argue that they are quite relevant to routine image interpretation and reporting. |
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Authors:
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Chris Sistrom |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Academic radiology Volume: 13 ISSN: 1076-6332 ISO Abbreviation: Acad Radiol Publication Date: 2006 May |
Date Detail:
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Created Date: 2006-04-21 Completed Date: 2006-10-27 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9440159 Medline TA: Acad Radiol Country: United States |
Other Details:
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Languages: eng Pagination: 580-8 Citation Subset: IM |
Affiliation:
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Radiology, University of Florida Health Center, P.O. Box 100374, Gainesville, FL 32610, USA. sistrc@radiology.ufl.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Bayes Theorem Causality Decision Making* Decision Theory* Epidemiology* Evidence-Based Medicine* Mental Processes* Models, Statistical* Radiology* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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