dc.contributor.author |
Al-Askar H. |
|
dc.contributor.author |
Almurshedi R. |
|
dc.contributor.author |
Mustafina J. |
|
dc.contributor.author |
Al-Jumeily D. |
|
dc.contributor.author |
Hussain A. |
|
dc.date.accessioned |
2022-02-09T20:33:45Z |
|
dc.date.available |
2022-02-09T20:33:45Z |
|
dc.date.issued |
2021 |
|
dc.identifier.issn |
0302-9743 |
|
dc.identifier.uri |
https://dspace.kpfu.ru/xmlui/handle/net/169030 |
|
dc.description.abstract |
Skin cancer is classified as one of the most dangerous cancer. Malignant melanoma is one of the deadliest types of skin cancer. Early detection of malignant melanoma is essential for treatment, hence saving lives and can significantly help to achieve full recovery. Current method heavily relies on clinical examination along with supportive methods to reach the correct clinical diagnosis. This paper considers the use of Machine Learning tools in early detection of skin cancer. It also presents the results of the data analysis of Skin Lesions Distribution according to age and gender and localization. |
|
dc.relation.ispartofseries |
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|
dc.subject |
Deep learning |
|
dc.subject |
Early detection |
|
dc.subject |
Intelligent systems |
|
dc.subject |
Machine learning |
|
dc.subject |
Skin cancer |
|
dc.title |
AI in Skin Cancer Detection |
|
dc.type |
Conference Proceeding |
|
dc.relation.ispartofseries-volume |
12838 LNAI |
|
dc.collection |
Публикации сотрудников КФУ |
|
dc.relation.startpage |
301 |
|
dc.source.id |
SCOPUS03029743-2021-12838-SID85113742992 |
|