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

Joint Authors

Nicolas, Ruben
Fornells, Albert
Golobardes, Elisabet
Corral, Guiomar
Puig, Susana
Malvehy, Josep

Source

The Scientific World Journal

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-01-21

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

The number of melanoma cancer-related death has increased over the last few years due to the new solar habits.

Early diagnosis has become the best prevention method.

This work presents a melanoma diagnosis architecture based on the collaboration of several multilabel case-based reasoning subsystems called DERMA.

The system has to face up several challenges that include data characterization, pattern matching, reliable diagnosis, and self-explanation capabilities.

Experiments using subsystems specialized in confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis.

American Psychological Association (APA)

Nicolas, Ruben& Fornells, Albert& Golobardes, Elisabet& Corral, Guiomar& Puig, Susana& Malvehy, Josep. 2014. DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1049292

Modern Language Association (MLA)

Nicolas, Ruben…[et al.]. DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning. The Scientific World Journal No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1049292

American Medical Association (AMA)

Nicolas, Ruben& Fornells, Albert& Golobardes, Elisabet& Corral, Guiomar& Puig, Susana& Malvehy, Josep. DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1049292

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1049292