Pattern Discovery in Melanoma Domain Using Partitional Clustering
David Vernet, Rubén Nicolás-Sans, Elisabet Golobardes, Albert Fornells, Garriga Carles, Susana Puig, Josep Malvehy · Frontiers in artificial intelligence and applications · 2008
Nowadays melanoma is one of the most important cancers to study due to its social impact. This dermatologic cancer has increased its frequency and mortality during last years. In particular, mortality is around twenty percent in non early detected ones. For this reason, the aim of medical researchers is to improve the early diagnosis through a best melanoma characterization using pattern matching. This article presents a new way to create real melanoma patterns in order to improve the future treatment of the patients. The approach is a pattern discovery system based on the K-Means clustering method and validated by means of a Case-Based Classifier System.