- Tytuł:
- Deep Learning Can Improve Early Skin Cancer Detection
- Autorzy:
-
Mohamed, Abeer
Mohamed, Wael A.
Zekry, Abdel Halim - Tematy:
-
technology
dermoscopic lesions
convolutional
neural network
ISIC dataset
deep learning
neural networks - Pokaż więcej
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Powiązania:
- https://bibliotekanauki.pl/articles/963798.pdf Link otwiera się w nowym oknie
- Opis:
- Skin cancer is the most common form of cancer affecting humans. Melanoma is the most dangerous type of skin cancer; and early diagnosis is extremely vital in curing the disease. So far, the human knowledge in this field is very limited, thus, developing a mechanism capable of identifying the disease early on can save lives, reduce intervention and cut unnecessary costs. In this paper, the researchers developed a new learning technique to classify skin lesions, with the purpose of observing and identifying the presence of melanoma. This new technique is based on a convolutional neural network solution with multiple configurations; where the researchers employed an International Skin Imaging Collaboration (ISIC) dataset. Optimal results are achieved through a convolutional neural network composed of 14 layers. This proposed system can successfully and reliably predict the correct classification of dermoscopic lesions with 97.78% accuracy.
- Dostawca treści:
- Biblioteka Nauki
Artykuł