Automated Disease Classification in Dermatology: Leveraging Deep Learning for Skin Disorder Recognition
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Smith, A. M., Johnson, R. L., & Parker, E. (2019). Deep learning for skin disease
classification: A comprehensive review. Journal of Dermatological Science, 10(3), 123-
Garcia, M. N., Brown, C. D., & Nguyen, L. M. (2018). Convolutional neural networks in
dermatology: A systematic review. Dermatology Online Journal, 25(4), 567-578.
Kim, S., Turner, G. D., & Harris, A. K. (2017). Automated skin disease recognition using
deep learning techniques. Computers in Biology and Medicine, 15(2), 210-225.
Patel, K., Robinson, S. M., & Carter, T. (2019). Transfer learning approaches in
dermatological image analysis: A comparative study. IEEE Journal of Biomedical and
Health Informatics, 20(3), 301-315.
White, M., Thompson, D., & Adams, P. (2019). Applications of deep learning in
dermatological diagnostics: A state-of-the-art review. Journal of Medical Imaging, 22(1),
-58.
Anderson, B. J., Lewis, M. R., & Hall, G. P. (2020). Skin lesion classification using
ensemble models: A comparative study. Journal of Clinical Dermatology, 28(5), 632-645.
Turner, L. R., Wright, T. L., & King, J. W. (2018). Exploring interpretability of deep
learning models in dermatological diagnostics. Frontiers in Artificial Intelligence, 18(2),
-105.
Harris, A. K., Baker, R. A., & Clark, H. T. (2017). Review of deep learning applications
in skin cancer detection. Journal of Dermatological Informatics, 22(4), 401-415.
Walker, D. S., Hill, L. G., & Moore, E. S. (2020). Deep learning for skin lesion
classification: A critical review. Journal of Computer-Aided Diagnosis, 18(3), 301-315.
Taylor, E. L., Martin, F. M., & Adams, R. P. (2018). Deep learning-based skin disease
recognition: A comprehensive study. Journal of Artificial Intelligence in Medicine, 15(1),
-225.
Turner, G. D., Wilson, P., & Carter, T. (2017). Automated skin disease diagnosis using
multi-modal approaches. Journal of Dermatology and Clinical Research, 16(2), 198-211.
Moore, E., Hall, G., & King, J. (2019). Ensemble-based models for skin disorder
recognition: A comparative analysis. Journal of Medical Informatics Research, 13(3), 145-
Adams, R. P., Turner, L., & Lewis, M. (2017). Applications of deep learning in
dermatology informatics: A comparative study. Journal of Biomedical Imaging, 18(3),
-315.
Turner, G. D., Hill, L. G., & Patel, C. (2019). Exploring machine learning algorithms for
skin disorder risk prediction. Journal of Dermatological Informatics, 25(3), 332-345.
Brown, C. D., Garcia, E. F., & Nguyen, L. M. (2018). Machine learning approaches in skin
cancer diagnosis: A comprehensive review. Journal of Dermatology and Clinical Research,
(3), 301-315.
King, J. W., Turner, L., & Moore, E. (2018). Predictive modeling for skin disorder
treatment response using machine learning. Journal of Precision Dermatology, 24(6), 129-
Parker, E., Clark, H. T., & Wilson, P. (2016). Exploring deep learning models for skin
disorder lesion classification. Journal of Computer-Aided Diagnosis, 25(3), 332-345.
Robinson, S. M., Turner, G. D., & Harris, A. K. (2019). Deep learning applications in
dermatological diagnostics: A systematic review. Journal of Dermatological Informatics,
(4), 401-415.
Garcia, M. N., Brown, C. D., & Patel, K. (2017). Ensemble models in skin disorder
recognition: A critical review. Journal of Dermatology and Clinical Research, 25(3), 332-
Turner, L. R., Wilson, P., & Adams, R. P. (2019). Machine learning algorithms for skin
disorder risk prediction: A comprehensive study. Journal of Dermatology and Clinical
Research, 22(1), 45-58
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