SVM and Neural Networks comparison in mammographic CAD

  title={SVM and Neural Networks comparison in mammographic CAD},
  author={C. J. Garcia-Orellana and Ramon Gallardo-Caballero and Miguel Macias-Macias and Horacio M. Gonzalez-Velasco},
  journal={2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
The purpose of this work is to compare the performance of support vector machines (SVM) and multi-layer perceptron (MLP) in the task of detection and diagnosis of microcalcification clusters in mammograms (MCCs). As data source, the "digital database for screening mammography"; (DDSM) was used. The results show a similar performance for SVM and MLP, in both tasks, detection and diagnosis (slightly better for MLP in detection). 

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