Linked Life Data

20027381

Source:http://linkedlifedata.com/resource/pubmed/id/20027381

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2010-1-11
pubmed:abstractText
Bayesian anomaly detection computes posterior probabilities of anomalous events by combining prior beliefs and evidence from data. However, the specification of prior probabilities can be challenging. This paper describes a Bayesian prior in the context of disease outbreak detection. The goal is to provide a meaningful, easy-to-use prior that yields a posterior probability of an outbreak that performs at least as well as a standard frequentist approach. If this goal is achieved, the resulting posterior could be usefully incorporated into a decision analysis about how to act in light of a possible disease outbreak.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0026-1270
pubmed:author
pubmed:issnType
Print
pubmed:volume
49
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
44-53
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
A new prior for bayesian anomaly detection: application to biosurveillance.
pubmed:affiliation
Lister Hill National Center for Biomedical Communications, Building 38A, 9N912A, National Institute of Health, Bethesda, Maryland 20894, USA. yanna.shen@nih.gov
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.