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COBRA: An Evolved Online Tool for Mammography Interpretation

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Computational Methods in Neural Modeling (IWANN 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2686))

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Abstract

This paper presents an evolved rule-based tool for mammography interpretation denominated “COBRA: Catalonia online breastcancer risk assessor.” COBRA is designed to aid radiologists in the interpretation of mammography to decide whether to perform a biopsy on a patient or not while providing a human-friendly explanation of the underlying reasoning. From a diagnostic point of view, the tool exhibits high performance measures (i.e., sensitivity, specificity, and positive predictive value). From an interpretability point of view, COBRA’s behavior is explained by only 14 rules containing, in average, 2.73 conditions perrule.

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References

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Author information

Authors and Affiliations

  1. Swiss Federal Institute of Technology Lausanne - EPFL, Switzerland

    Carlos-Andrés Peña-Reyes & Eduardo Sanchez

  2. Centro Nacional de Microelectrónica, Barcelona, Spain

    Rosa Villa

  3. Duran i Reynals Hospital, Barcelona, Spain

    Luis Prieto

Authors
  1. Carlos-Andrés Peña-Reyes
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  2. Rosa Villa
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  3. Luis Prieto
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  4. Eduardo Sanchez
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Editor information

Editors and Affiliations

  1. E.T.S. de Ingeniería Informática Departamento de Inteligencia Artificial, Universidad Nacional de Educación a Distancia, Juan del Rosal, 16, 28040, Madrid, Spain

    José Mira  & José R. Álvarez  & 

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© 2003 Springer-Verlag Berlin Heidelberg

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Peña-Reyes, CA., Villa, R., Prieto, L., Sanchez, E. (2003). COBRA: An Evolved Online Tool for Mammography Interpretation. In: Mira, J., Álvarez, J.R. (eds) Computational Methods in Neural Modeling. IWANN 2003. Lecture Notes in Computer Science, vol 2686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44868-3_92

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  • DOI: https://doi.org/10.1007/3-540-44868-3_92

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40210-7

  • Online ISBN: 978-3-540-44868-6

  • eBook Packages: Springer Book Archive

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