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An Exploratory Analysis of ML Models in CADx Design

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dc.contributor.advisorRussakovsky, Olga
dc.contributor.authorTeferi, Emmanuel
dc.date.accessioned2020-10-01T21:26:22Z
dc.date.accessioned2026-09-29T21:55:14Z
dc.date.available2020-10-01T21:26:22Z
dc.date.available2026-09-29T21:55:14Z
dc.date.issued2020-10-01
dc.description.abstractThe goal of this study is to explore classification models that could be potentially used in Computer Aided Diagnosis (CADx). The performances of models with different feature extraction methods, feature representations, and classifier combinations are tested and analyzed. None of the models explored in this study are viable options for CADx models. The results may reveal useful information regarding future improvement of CADx models.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp019880vv028
dc.identifier.urihttps://theses-dissertations.princeton.edu/handle/88435/dsp019880vv028
dc.language.isoen
dc.titleAn Exploratory Analysis of ML Models in CADx Design
dc.typePrinceton University Senior Theses
dspace.entity.typePublication
pu.certificateNone
pu.contributor.authorid961269314
pu.date.classyear2020
pu.departmentComputer Science
pu.pdf.coverpageSeniorThesisCoverPage

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