Data: A Comprehensive Review of Artificial Intelligence Algorithms and Applications in Melanoma Diagnosis
| dc.contributor.author | Yalcin, Doruk | |
| dc.contributor.orcid | 0009-0001-0568-8778 | |
| dc.date.accessioned | 2025-10-24T11:34:22Z | |
| dc.date.issued | 2024-01-01 | |
| dc.description.abstract | Melanoma, 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.uri | https://dx.doi.org/10.7910/dvn/3ns35j | |
| dc.identifier.doi | 10.7910/dvn/3ns35j | |
| dc.identifier.openaire | doi_________::eb137f36e84be4b0ce7db51469929937 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14288/31245 | |
| dc.publisher | Harvard Dataverse | |
| dc.rights | OPEN | |
| dc.subject | Machine Learning | |
| dc.subject | Engineering | |
| dc.subject | Deep Learning | |
| dc.subject | Dermatology | |
| dc.subject | Melanoma | |
| dc.subject | Skin Cancer | |
| dc.title | A Comprehensive Review of Artificial Intelligence Algorithms and Applications in Melanoma Diagnosis | |
| dc.type | Dataset | |
| dspace.entity.type | Data | |
| local.import.source | OpenAire |
