Using Ensemble-Based Reasoning to Help Experts in Melanoma Diagnosis

Authors:
Ruben Nicolas;Elisabet Golobardes;Albert Fornells;Sonia Segura;Susana Puig;Cristina Carrera;Joseph Palou;Josep Malvehy
Affiliations:
Grup de Recerca en Sistemes Intel.ligents, Enginyeria i Arquitectura La Salle-Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona, {rnicolas,elisabet,afornells}@salle.url.edu;Grup de Recerca en Sistemes Intel.ligents, Enginyeria i Arquitectura La Salle-Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona, {rnicolas,elisabet,afornells}@salle.url.edu;Grup de Recerca en Sistemes Intel.ligents, Enginyeria i Arquitectura La Salle-Universitat Ramon Llull, Quatre Camins 2, 08022 Barcelona, {rnicolas,elisabet,afornells}@salle.url.edu;Dermatology Department of Hospital del Mar, Passeig Marítim 25-29, 08003 Barcelona, ssegura@imas.imim.es;Melanoma Unit, Dermatology Department, Hospital Clinic i Provincial de Barcelona, IDIBAPS, {spuig,ccarrera,jpalou,jmalvehy}@clinic.ub.es;Melanoma Unit, Dermatology Department, Hospital Clinic i Provincial de Barcelona, IDIBAPS, {spuig,ccarrera,jpalou,jmalvehy}@clinic.ub.es;Melanoma Unit, Dermatology Department, Hospital Clinic i Provincial de Barcelona, IDIBAPS, {spuig,ccarrera,jpalou,jmalvehy}@clinic.ub.es;Melanoma Unit, Dermatology Department, Hospital Clinic i Provincial de Barcelona, IDIBAPS, {spuig,ccarrera,jpalou,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

Citing 11
Cited 0

Case-based reasoning: foundational issues, methodological variations, and system approaches

AI Communications
Method combination for document filtering

SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Solving regression problems with rule-based ensemble classifiers

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
A streaming ensemble algorithm (SEA) for large-scale classification

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants

Machine Learning
Empirical comparisons of various voting methods in bagging

Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Comparing Bayes model averaging and stacking when model approximation error cannot be ignored

The Journal of Machine Learning Research
Diverse ensembles for active learning

ICML '04 Proceedings of the twenty-first international conference on Machine learning
Boosting SVM classifiers by ensemble

WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Multiclass Boosting for Weak Classifiers

The Journal of Machine Learning Research
LCSE: learning classifier system ensemble for incremental medical instances

IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

New habits in solar exposure have caused an important increase of melanoma cancer during the last few years. However, recent studies demonstrate that early diagnosis drastically improves the treatment of this illness. This work presents a platform called MEDIBE that helps experts to diagnose melanoma. MEDIBE is an ensemble-based reasoning system that uses two of the most important non-invasive image techniques: Reflectance Confocal Microscopy and Dermatoscopy. The combination of both image source improves the reliability of diagnosis.