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Systematic Literature Reviews in Software Engineering—A Systematic Literature Review

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Implementing Machine Learning in Health Care — Addressing Ethical Challenges

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Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

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Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks

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PH2 - A dermoscopic image database for research and benchmarking

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DSCC_Net: multi-classification deep learning models for diagnosing of skin cancer using dermoscopic images

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FCN-Based DenseNet Framework for Automated Detection and Classification of Skin Lesions in Dermoscopy Images

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Classification of skin cancer from dermoscopic images using deep neural network architectures

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A review on brain tumor segmentation based on deep learning methods with federated learning techniques

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AI-Powered Diagnosis of Skin Cancer: A Contemporary Review, Open Challenges and Future Research Directions

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SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images

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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer

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DMFL_Net: A Federated Learning-Based Framework for the Classification of COVID-19 from Multiple Chest Diseases Using X-rays

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New Trends in Melanoma Detection Using Neural Networks: A Systematic Review

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SNC_Net: Skin Cancer Detection by Integrating Handcrafted and Deep Learning-Based Features Using Dermoscopy Images

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Detection of melanoma in dermoscopic images by integrating features extracted using handcrafted and deep learning models

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A Traffic Analysis and Node Categorization- Aware Machine Learning-Integrated Framework for Cybersecurity Intrusion Detection and Prevention of WSNs in Smart Grids

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A hybrid approach for melanoma classification using ensemble machine learning techniques with deep transfer learning

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Detection and Classification of Melanoma Skin Cancer Using Image Processing Technique

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SkinNet-INIO: Multiclass Skin Lesion Localization and Classification Using Fusion-Assisted Deep Neural Networks and Improved Nature-Inspired Optimization Algorithm

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A lightweight deep convolutional neural network model for skin cancer image classification

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BDCNet: multi-classification convolutional neural network model for classification of COVID-19, pneumonia, and lung cancer from chest radiographs

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DVFNet: a deep feature fusion-based model for the multiclassification of skin cancer utilizing dermoscopy images

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Federated and Transfer Learning Methods for the Classification of Melanoma and Nonmelanoma Skin Cancers: A Prospective Study

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Smart Contracts in the Construction Industry: A Systematic Review

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Advances in database systems education: Methods, tools, curricula, and way forward

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Deep Learning for Melanoma Detection: A Deep Learning Approach to Differentiating Malignant Melanoma from Benign Melanocytic Nevi

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Automatic melanoma and non-melanoma skin cancer diagnosis using advanced adaptive fine-tuned convolution neural networks

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IARS SegNet: Interpretable Attention Residual Skip Connection SegNet for Melanoma Segmentation

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Quantum Machine Learning based Computer Aided Diagnosis for Skin Cancer Detection: A Statistical Performance Analysis over Classical Approach

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Melanoma Skin Cancer Disease Detection Using Convolutional Neural Network

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Convolutional Neural Network and Fuzzy Logic-based Hybrid Melanoma Diagnosis System

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Automated Psoriasis Detection using Deep Learning

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Ethical Guidelines for Artificial Intelligence: A Systematic Literature Review

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Deep Learning for Melanoma Detection with Testing Time Data Augmentation

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Handling dataset dependence with model ensembles for skin lesion classification from dermoscopic and clinical images

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Skin Cancer Detection and Classification Through Medical Image Analysis Using EfficientNet

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Early Detection Of Melanoma Skin Cancer Using Efficient Netb6

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Performance Improvement of Melanoma Detection Using a Multi-Network System Based on Decision Fusion

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MobileNet-Enhanced Skin Cancer Detection and Classification Using Dermatoscopic Images

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MIoT Based Skin Cancer Detection Using Bregman Recurrent Deep Learning

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