SyntDiaNet and RadiomixNet Integrated Framework of Feature Extraction Transfer Learning GAN and Edge Diagnosis of Lung Infections

dc.contributor.guideProf. Siva Sankar Yellampalli
dc.coverage.spatial
dc.creator.researcherRAHUL GOWTHAM POOLA
dc.date.accessioned2025-02-04T06:19:40Z
dc.date.available2025-02-04T06:19:40Z
dc.date.awarded2024
dc.date.completed2024
dc.date.registered2020
dc.description.abstractIn the dynamic field of infectious diseases, the pursuit of novel approaches to enhance newlinediagnostic efficiency has become increasingly essential. This thesis report presents newlinemultiple novel approaches to address the requirements by exploring the collaborative newlinepower of artificial intelligence with state-of-the-art medical imaging techniques. By newlineexploring the intricacies of disease pathology and diagnostic imaging, this research newlineseeks to unlock new frontiers in early detection and accurate diagnosis, ultimately newlinepaving the way for enhanced disease management and improved clinical outcomes. newlineIn response to the critical need for advanced diagnostic methods in the face of escalating newlineinfectious diseases, this thesis explore AI and medical imaging technologies. The newlinerapid emergence of infectious diseases such as COVID-19 and pneumonia has underscored newlinethe pressing need for efficient and precise diagnostic methods within global newlinehealthcare systems. Traditional methods often prove inadequate in meeting the demands newlineof timely diagnosis, prompting researchers to explore innovative approaches newlineleveraging artificial intelligence and medical imaging technologies. This thesis provides newlinecomprehensive research into the application of AI-driven medical imaging for newlinethe early diagnosis of infectious diseases, with a particular focus on COVID-19 and newlinepneumonia. newline
dc.description.note
dc.format.accompanyingmaterialDVD
dc.format.dimensions
dc.format.extent
dc.identifier.researcherid
dc.identifier.urihttp://hdl.handle.net/10603/619847
dc.languageEnglish
dc.publisher.institutionElectronics and Communication Engineering
dc.publisher.placeMangalagiri
dc.publisher.universitySRM University- AP
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.titleSyntDiaNet and RadiomixNet Integrated Framework of Feature Extraction Transfer Learning GAN and Edge Diagnosis of Lung Infections
dc.title.alternative
dc.type.degreePh.D.

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