AI-Based Early Lung Cancer Diagnostic Framework

dc.contributor.authorKhaled Mohamed Kamal Elborai, Zeina
dc.contributor.authorMostafa Abdelmoniem Mostafa, Elham
dc.date.accessioned2022-07-24T13:02:33Z
dc.date.available2022-07-24T13:02:33Z
dc.date.issued2022
dc.description.abstractDue to the limitations of human vision, it is simple for radiologists to miss small malignant tumors. At the initial screening, up to 35% of lung nodules are missed. Deep-learning systems understand what a tumor is from real-world instances rather than searching for tumor features that a programmer has predefined in advance. Researchers provide the systems with a huge data set made up of lung CT scans of thousands of individuals, some of whom had cancer and others of whom did. The ability of the computers to identify between lung tumors and benign increases with the number of training scans they have seen. And they perform this task more precisely than earlier, non-AI systems.en_US
dc.description.sponsorshipDr/ Samer Ibrahim Mohameden_US
dc.identifier.citationFaculty Of Engineering Graduation Project 2020- 2022en_US
dc.identifier.urihttps://2u.pw/LmUBY
dc.language.isoenen_US
dc.publisherMSAen_US
dc.relation.ispartofseriesFaculty Of Engineering Graduation Project 2020- 2022;
dc.subjectuniversity of modern sciences and artsen_US
dc.subjectجامعة أكتوبر للعلوم الحديثة و الأدابen_US
dc.subjectMSA universityen_US
dc.subjectOctober university for modern sciences and artsen_US
dc.subjectLung Canceren_US
dc.titleAI-Based Early Lung Cancer Diagnostic Frameworken_US
dc.typeOtheren_US

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