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Machine learning-based classification of skin cancer hyperspectral images

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Genetic programming for automatic skin cancer image classification

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Web-based skin cancer assessment and classification using machine learning and mobile computerized adaptive testing in a Rasch model: Development study

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Classification of human skin cancer using Stokes-Mueller decomposition method and artificial intelligence models

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Hybrid convolutional neural networks with SVM classifier for classification of skin cancer

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CHASHNIt for enhancing skin disease classification using GAN augmented hybrid model with LIME and SHAP based XAI heatmaps

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FixCaps: An improved capsules network for diagnosis of skin cancer

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Unit-vise: Deep shallow unit-vise residual neural networks with transition layer for expert level skin cancer classification

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Melanoma is skin deep: A 3D reconstruction technique for computerized dermoscopic skin lesion classification

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A GAN-based data augmentation method for imbalanced multi-class skin lesion classification

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Region-of-interest based transfer learning assisted framework for skin cancer detection

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Four-class classification of skin lesions with task decomposition strategy

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DeepSkin: A deep learning approach for skin cancer classification

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Classification of melanoma and nevus in digital images for diagnosis of skin cancer

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Noninvasive real-time automated skin lesion analysis system for melanoma early detection and prevention

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Multi-class skin lesion detection and classification via teledermatology

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FCN-based DenseNet framework for automated detection and classification of skin lesions in dermoscopy images

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Towards improving skin cancer diagnosis by integrating microarray and RNA-seq datasets

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Early detection of multiclass skin lesions using transfer learning-based incepX-Ensemble model

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A hybrid deep learning approach for skin cancer classification using swin transformer and dense group shuffle non-local attention network

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SHERA: SHAP-enhanced resource allocation for VM scheduling and efficient cloud computing

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