Terry's nail identification: A novel machine learning approach
Yazarlar (4)
| Makale Türü | Özgün Makale (Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale) | ||
| Dergi Adı | International Conference on Engineering, Science, Technology, and Management | ||
| Makale Dili | – | Basım Tarihi | 01-2023 |
| Makale Linki | https://www.researchgate.net/profile/Syed-Sarwar/publication/376390124_Molecular_Dynamics_Study_of_Carbazochrome_Encapsulation_in_Single-Walled_Carbon_Nanotube/links/6575caa0fc4b416622b1fec5/Molecular-Dynamics-Study-of-Carbazochrome-Encapsulation-in- | ||
| UAK Araştırma Alanları |
Fiziksel Kimya
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| Özet |
| Terry's nail is a condition in which the nail seems to have a kind of leukonychia that is differentiated by the ground glass occlusion of the nail, the pink nail bed at the distal border, and the loss of the lunula. The objective of this study is to use a decision tree-based machine learning algorithm to classify Terry's nails and healthy nails. The study has been executed with the collection of a dataset of a total of 87 nail images. It consists of 48 images of normal, healthy nails and 39 images of Terry's nails. The images are categorized using feature extraction techniques and a decision tree classifier algorithm to help with the classification. A total of 27 nail images were evaluated, yielding an accuracy of 82.5%. As per the results, decision tree approaches have the capability of achieving robust categorization and efficiency. |
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