September 25, 2025Deleted Journal

Machine learning and deep learning approaches to classify skin diseases based on medical images

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ABAkhmadkhon BobokhonovSamarkand State University named after Sharof Rashidov LKL. Khuramov ARAldeniz RashidovTechnical University of Gabrovo

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Implication

This analysis evaluates the effectiveness of machine learning and deep learning for skin disease classification, indicating potential advancements in diagnosis accuracy.

Key Points

Machine learning and deep learning techniques improve the classification of skin diseases, offering faster diagnostics.
The study identifies various models and algorithms for accurate classification using medical images.
This research highlights the role of intelligent systems in early detection of skin diseases, potentially reducing healthcare costs.
Future research could further enhance diagnostic accuracy through advanced algorithms and larger image datasets.

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Bobokhonov et al. (2025) studied this question.

synapsesocial.com/papers/68d5e1ffbd7882ccb9b864f2 https://doi.org/10.59251/2181-3973.2025.v1.138.1.3417

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Implication

This analysis evaluates the effectiveness of machine learning and deep learning for skin disease classification, indicating potential advancements in diagnosis accuracy.

Machine learning and deep learning approaches to classify skin diseases based on medical images

Discussion

Member takes

Implication

Key Points

Cite This Study

Machine learning and deep learning approaches to classify skin diseases based on medical images

Discussion

Member takes

Implication

Key Points

Cite This Study

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