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Artificial intelligence assisted drop pattern analysis and RNAseq profiling for early diagnosis and follow-up of bladder cancer

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dc.contributor.advisorGözüaçık, Devrim
dc.contributor.departmentGraduate School of Health Sciences
dc.contributor.kuauthorDemir, Ramiz
dc.contributor.programCellular and Molecular Medicine
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF HEALTH SCIENCES
dc.coverage.spatialİstanbul
dc.date.accessioned2024-11-09T22:36:57Z
dc.date.issued2023
dc.format.extentxx, 101 leaves : illustrations ; 30 cm.
dc.identifier.urihttps://hdl.handle.net/20.500.14288/5786
dc.keywordsArtificial intelligence
dc.keywordsDeep learning
dc.keywordsBladder cancer
dc.keywordsDiagnosis
dc.keywordsFollow-up
dc.keywordsRNA sequencing
dc.language.isoeng
dc.publisherKoç University
dc.relation.collectionKU Theses and Dissertations
dc.rightsrestrictedAccess
dc.rights.copyrightsnote© All Rights Reserved. Accessible to Koç University Affiliated Users Only!
dc.subjectArtificial intelligence, Medical applications
dc.subjectIntelligent control systems
dc.subjectExpert systems (Computer science)
dc.subjectDecision support systems
dc.subjectBiomedical technology
dc.subjectCancer, Prevention
dc.subjectBladder, Cancer
dc.subjectUrinary bladder neoplasms
dc.titleArtificial intelligence assisted drop pattern analysis and RNAseq profiling for early diagnosis and follow-up of bladder cancer
dc.typeThesis
dspace.entity.typePublication
local.contributor.kuauthorDemir, Ramiz
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