DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning

Abstract

The number of melanoma cancer-related death has increased over the last few years due to the new solar habits. Early diagnosishas become the best prevention method. This work presents a melanoma diagnosis architecture based on the collaboration ofseveral multilabel case-based reasoning subsystems called DERMA. The system has to face up several challenges that include datacharacterization, pattern matching, reliable diagnosis, and self-explanation capabilities. Experiments using subsystems specializedin confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis.