Intelligent diagnosis of psoriasis vulgaris based on deep learning and improved fuzzy KMeans / 中国医学物理学杂志
Chinese Journal of Medical Physics
; (6): 253-257, 2024.
Article
en Zh
| WPRIM
| ID: wpr-1026219
Biblioteca responsable:
WPRO
ABSTRACT
In order to address issues such as the decline in diagnostic performance of deep learning models due to imbalanced data distribution in psoriasis vulgaris,a VGG13-based deep convolutional neural network model is proposed by integrating the processing capability of the improved fuzzy KMeans clustering algorithm for highly clustered complex data and the predictive capability of VGG13 deep convolutional neural network model.The model is applied to the diagnosis of psoriasis vulgaris,and the experimental results indicate that compared with VGG13 and resNet18,the proposed approach based on deep learning and improved fuzzy KMeans is more suitable for identifying psoriasis features.
Texto completo:
1
Base de datos:
WPRIM
Idioma:
Zh
Revista:
Chinese Journal of Medical Physics
Año:
2024
Tipo del documento:
Article