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dc.contributor.advisorCarty, Christopher P
dc.contributor.authorBai, Amelia
dc.date.accessioned2023-01-05T03:25:23Z
dc.date.available2023-01-05T03:25:23Z
dc.date.issued2022-12-15
dc.identifier.doi10.25904/1912/4725
dc.identifier.urihttp://hdl.handle.net/10072/420604
dc.description.abstractRetinopathy of prematurity (ROP) is a sight threatening proliferative retinal vascular disease affecting premature infants. Vision loss in ROP is preventable through the early identification and treatment of severe disease. Timely screening and accurate diagnosis is therefore crucial for the diagnosis of ROP, however, multiple challenges exist in current screening processes including limited access to expert ophthalmologists required for ROP screening, subjectivity of diagnosis and cost and time burdens involved in transporting infants to tertiary hospitals. Artificial intelligence (AI) has the potential to overcome current challenges in ROP diagnosis and may transform the way ROP is screened for and managed. Through innovative deep learning technology, a well-designed, well-validated detection algorithm may provide accessible, objective analysis of retinal images to assist expert ophthalmologists in detecting referrable ROP. This thesis will introduce readers to the pathophysiology and grading of ROP, evidence for current treatment guidelines and AI applications in ophthalmology. The systematic review will provide the background evidence into requirements for an accurate, reliable AI algorithm in ROP diagnosis and the validation of our AI algorithm, ROP.AI, will provide insight into the revolutionary diagnostic potential of this deep learning program. Finally, we will discuss future plans for ROP.AI including a methodology proposal to implement the algorithm into a prospective clinical trial for the diagnosis of ROP.en_US
dc.languageEnglish
dc.language.isoen
dc.publisherGriffith University
dc.publisher.placeBrisbane
dc.subject.keywordsretinopathy of prematurity (ROP)en_US
dc.subject.keywordsartificial intelligenceen_US
dc.subject.keywordsophthalmologyen_US
dc.titleA New Era in the Screening and Diagnosis of Retinopathy of Prematurity: the Application of Artificial Intelligenceen_US
dc.typeGriffith thesisen_US
gro.facultyGriffith Healthen_US
gro.rights.copyrightThe author owns the copyright in this thesis, unless stated otherwise.
gro.hasfulltextFull Text
dc.contributor.otheradvisorNghiem, Son H
dc.contributor.otheradvisorDai, Shuan
gro.identifier.gurtID000000029989en_US
gro.thesis.degreelevelThesis (Masters)en_US
gro.thesis.degreeprogramMaster of Medical Research (MMedRes)en_US
gro.departmentSchool of Pharmacy & Med Scien_US
gro.griffith.authorBai, Amelia


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