DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation-Reference-Cited by-同舟云学术

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DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation

Published:2022 Issue: Volume:28 Page:100819
ISSN:2352-9148
Container-title:Informatics in Medicine Unlocked
language:en
Short-container-title:Informatics in Medicine Unlocked

Author:

Hasan Md. Kamrul^ORCID,Elahi Md. Toufick E.,Alam Md. Ashraful^ORCID,Jawad Md. Tasnim^ORCID,Martí Robert^ORCID

Publisher

Elsevier BV

Subject

Health Informatics

Reference112 articles.

1. Epidemiology of skin cancer: update 2019;Leiter,2020

2. Skin cancer detection using non-invasive techniques;Narayanamurthy;RSC Adv,2018

3. Gender identity and lifetime prevalence of skin cancer in the United States;Singer;JAMA Dermatol,2020

4. Biomarkers in melanoma and non-melanoma skin cancer prevention and risk stratification;Trager;Exp Dermatol,2020

5. Cancer statistics, 2020;Siegel;CA: Cancer J Clin,2020

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1. A web-based mpox skin lesion detection system using state-of-the-art deep learning models considering racial diversity;Biomedical Signal Processing and Control;2024-12

2. SCINet: A Segmentation and Classification Interaction CNN Method for Arteriosclerotic Retinopathy Grading;Interdisciplinary Sciences: Computational Life Sciences;2024-09-02

3. Dermo‐Optimizer: Skin Lesion Classification Using Information‐Theoretic Deep Feature Fusion and Entropy‐Controlled Binary Bat Optimization;International Journal of Imaging Systems and Technology;2024-09

4. Integrating Multi‐Scale Feature Boundary Module and Feature Fusion With CNN for Accurate Skin Cancer Segmentation and Classification;International Journal of Imaging Systems and Technology;2024-09

5. Radiomic and deep learning analysis of dermoscopic images for skin lesion pattern decoding;Scientific Reports;2024-08-26

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