Testing for the difference in sensitivities of binary classifiers using survival analysis

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dc.contributor.authorKathare, Alfred
dc.contributor.authorOtieno, Argwings
dc.contributor.authorKimeli, Victor
dc.date.accessioned2021-05-11T08:48:13Z
dc.date.available2021-05-11T08:48:13Z
dc.date.issued2017
dc.descriptionPaper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June 2017, Strathmore University, Nairobi, Kenya.en_US
dc.description.abstractSensitivity is an important measure of the performance of a binary classifier in a disease control program among populations at risk. Where one has to choose between binary classifiers, on basis of their sensitivities, a test grounded on the theory is important for viability of the test results. The commonly used procedure namely the area under the receiver operating characteristic curve does not only lack strong theoretical basis but also trades the sensitivity of a classifier with its specificity. Also, the use of relative sensitivity is limited to comparison at single cut-off point of the classifiers. In this study was we provide a procedure for testing for the difference in sensitivities of two or more binary classifiers over a set of cutoffs without reference to their specificities. By observing the cumulative sensitivities over ordered cut-offs, we defined the survival function of the diseased individuals. Low sensitivity results to high survivability. To test for the difference in sensitivities we tested for the difference of the survival curve using the log-rank test. We subjected our approach to two pancreatic cancer classifiers and the test results show that the two were statistically difference. Further studies should focus on survival curves that close at some point.en_US
dc.description.sponsorshipUniversity of Eldoreten_US
dc.identifier.urihttp://hdl.handle.net/11071/11808
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectBinary classifieren_US
dc.subjectSensitivityen_US
dc.subjectSurvival functionen_US
dc.subjectRisk of failureen_US
dc.subject“Diseased” subjecten_US
dc.subject“Non-diseased” subjecten_US
dc.titleTesting for the difference in sensitivities of binary classifiers using survival analysisen_US
dc.typeArticleen_US
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