Data:
A Comprehensive Review of Artificial Intelligence Algorithms and Applications in Melanoma Diagnosis

dc.contributor.authorYalcin, Doruk
dc.contributor.orcid0009-0001-0568-8778
dc.date.accessioned2025-10-24T11:34:22Z
dc.date.issued2024-01-01
dc.description.abstractMelanoma, a lethal form of skin cancer, poses a significant health risk worldwide with rising incident rates. The usage of Artificial Intelligence (AI) tools in dermatology for melanoma detection can help curb the demand for accurate and efficient diagnosis of the disease. This review examines the current state of AI, Machine Learning (ML), and Deep Learning (DL) applications in the identification of melanomas through the analysis of various studies that have demonstrated the potential of these technologies that could outperform traditional methods and provide life-saving diagnoses. The primary usage of Convolutional Neural Networks (CNNs) has the potential to completely revolutionize the field of dermatological diagnosis.
dc.description.urihttps://dx.doi.org/10.7910/dvn/3ns35j
dc.identifier.doi10.7910/dvn/3ns35j
dc.identifier.openairedoi_________::eb137f36e84be4b0ce7db51469929937
dc.identifier.urihttps://hdl.handle.net/20.500.14288/31245
dc.publisherHarvard Dataverse
dc.rightsOPEN
dc.subjectMachine Learning
dc.subjectEngineering
dc.subjectDeep Learning
dc.subjectDermatology
dc.subjectMelanoma
dc.subjectSkin Cancer
dc.titleA Comprehensive Review of Artificial Intelligence Algorithms and Applications in Melanoma Diagnosis
dc.typeDataset
dspace.entity.typeData
local.import.sourceOpenAire

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