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Classifier performance prediction for computerâ aided diagnosis using a limited dataset
dc.contributor.authorSahiner, Berkman
dc.contributor.authorChan, Heang‐ping
dc.contributor.authorHadjiiski, Lubomir
dc.date.accessioned2017-01-06T20:48:49Z
dc.date.available2017-01-06T20:48:49Z
dc.date.issued2008-04
dc.identifier.citationSahiner, Berkman; Chan, Heang‐ping ; Hadjiiski, Lubomir (2008). "Classifier performance prediction for computerâ aided diagnosis using a limited dataset." Medical Physics 35(4): 1559-1570.
dc.identifier.issn0094-2405
dc.identifier.issn2473-4209
dc.identifier.urihttps://hdl.handle.net/2027.42/134979
dc.publisherAmerican Association of Physicists in Medicine
dc.publisherWiley Periodicals, Inc.
dc.subject.otherPattern recognition
dc.subject.otherComputerâ aided diagnosis
dc.subject.otherMonte Carlo simulations
dc.subject.otherNeural networks, fuzzy logic, artificial intelligence
dc.subject.otherApproximations and expansions
dc.subject.othercovariance matrices
dc.subject.otherlearning (artificial intelligence)
dc.subject.othermean square error methods
dc.subject.othermedical diagnostic computing
dc.subject.otherMonte Carlo methods
dc.subject.otherpattern classification
dc.subject.othersampling methods
dc.subject.othersensitivity analysis
dc.subject.otherclassifier performance
dc.subject.otherresampling
dc.subject.otherbootstrap
dc.subject.otherfinite sample size
dc.subject.otherTesting procedures
dc.subject.otherMonte Carlo methods
dc.subject.otherComputer aided diagnosis
dc.subject.otherLaser Doppler velocimetry
dc.subject.otherExperiment design
dc.subject.otherLinear regression
dc.subject.otherVector calculus
dc.subject.otherStatistical properties
dc.subject.otherMammography
dc.titleClassifier performance prediction for computerâ aided diagnosis using a limited dataset
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelMedicine (General)
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.contributor.affiliationumDepartment of Radiology, University of Michigan, Ann Arbor, Michigan 48109
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/134979/1/mp8757.pdf
dc.identifier.doi10.1118/1.2868757
dc.identifier.sourceMedical Physics
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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