An ensemble-based convolutional neural network model powered by a genetic algorithm for melanoma diagnosis

Key Points

• Melanoma diagnosis accuracy significantly increased with the genetic algorithm-based convolutional neural network model.
• The ensemble model achieved an accuracy rate of 95% across 500 skin image samples.
• Analysis utilized convolutional neural networks combined with genetic algorithm optimization for feature selection.
• Findings highlight the potential for improved melanoma detection using advanced machine learning techniques.