Identification of Variegated Coloring in Skin Tumors: Neural Network vs. Rule-Based Induction Methods

Ajaya Durg
William V. Stoecker, Missouri University of Science and Technology
J. P. Cookson
Scott E. Umbaugh
Randy Hays Moss, Missouri University of Science and Technology

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The use of neural networks for automatic identification of variegated coloring, which is believed to be one of the most predictive features for malignant melanoma, is described. The Nestor development system (NDS) was chosen for neural network implementation. At the heart of NDS is a three-layer neural network called a restricted Coulomb energy (RCE) network. The learning scheme and the database for detection of variegated coloring are discussed. Results are reported