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dc.contributor.authorWelhenge, Anuradhi
dc.date.accessioned2023-02-02T07:03:06Z
dc.date.available2023-02-02T07:03:06Z
dc.date.issued2022
dc.identifier.citationWelhenge, A. 2022. Deep learning based breast cancer detection system using fog computing. Journal of Discrete Mathematical Sciences and Cryptography. 25 (3): pp. 661-669.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/90317
dc.identifier.doi10.1080/09720529.2021.2014130
dc.description.abstract

Among the different types of cancers, more women are suffering from breast cancer. Breast cancer can be identified by mammograms or using ultrasounds. Early detection of the cancer can be used to minimize the complexities the women will face. Deep learning based techniques such as convolutional neural networks (CNN) are used to detect the cancer from mammograms or ultrasound scans. In this study, VGGNet based CNN is used to detect the cancer cells. A novel architecture for collecting, processing and storing of patient data is proposed in this study involving a fog layer. This study achieved a high accuracy, sensitivity and specificity compared to previous studies.

dc.titleDeep learning based breast cancer detection system using fog computing
dc.typeJournal Article
dcterms.source.volume25
dcterms.source.number3
dcterms.source.startPage661
dcterms.source.endPage669
dcterms.source.issn0972-0529
dcterms.source.titleJournal of Discrete Mathematical Sciences and Cryptography
dc.date.updated2023-02-02T07:03:06Z
curtin.departmentSchool of Elec Eng, Comp and Math Sci (EECMS)
curtin.accessStatusFulltext not available
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidWelhenge, Anuradhi [0000-0001-9219-2246]
curtin.contributor.scopusauthoridWelhenge, Anuradhi [56604130200]


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