Pattern Discovery in Melanoma Domain Using Partitional Clustering

  • Authors:

  • David Vernet;Ruben Nicolas;Elisabet Golobardes;Albert Fornells;Carles Garriga;Susana Puig;Josep Malvehy

  • Affiliations:

  • Grup de Recerca en Sistemes Intel·ligents, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona (Spain), {dave,rnicolas,elisabet,afornells,cgarriga}@s ...;Grup de Recerca en Sistemes Intel·ligents, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona (Spain), {dave,rnicolas,elisabet,afornells,cgarriga}@s ...;Grup de Recerca en Sistemes Intel·ligents, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona (Spain), {dave,rnicolas,elisabet,afornells,cgarriga}@s ...;Grup de Recerca en Sistemes Intel·ligents, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona (Spain), {dave,rnicolas,elisabet,afornells,cgarriga}@s ...;Grup de Recerca en Sistemes Intel·ligents, Enginyeria i Arquitectura La Salle, Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona (Spain), {dave,rnicolas,elisabet,afornells,cgarriga}@s ...;Melanoma Unit, Dermatology Department, IDIBAPS, U726 CIBERER, ISCIII, Hospital Clinic i Provincial de Barcelona (Spain), {spuig,jmalvehy}@clinic.ub.es;Melanoma Unit, Dermatology Department, IDIBAPS, U726 CIBERER, ISCIII, Hospital Clinic i Provincial de Barcelona (Spain), {spuig,jmalvehy}@clinic.ub.es

  • Venue:
  • Proceedings of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence
  • Year:
  • 2008

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Abstract

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.