Attention Cost-Sensitive Deep Learning-Based Approach for Skin Cancer Detection and Classification.

ABSTRACT: Deep learning-based models have been employed for the detection and classification of skin diseases through medical imaging. However, deep learning-based models are not effective for rare skin disease detection and classification. This is mainly due to the reason that rare skin disease has very a smaller number of data samples. Thus, the dataset will be highly imbalanced, and due to the bias in learning, most of the models give better performances. The deep learning models are not effective in detecting the affected tiny portions of skin disease in the overall regions of the image. This paper presents an attention-cost-sensitive deep learning-based feature fusion ensemble meta-classifier approach for skin cancer detection and classification. Cost weights are included in the deep learning m

SUBMITTER: Ravi V 

PROVIDER: S-EPMC9735681 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature