TY - GEN
T1 - Classification of difficult-to-diagnose microcalcifications using fuzzy neural network with convex sets
AU - Grohman, Wojciech M.
AU - Dhawan, Atam P.
PY - 1999
Y1 - 1999
N2 - A novel convex set based neuro-fuzzy algorithm for classification of difficult-to-diagnose instances of breast cancer is described in this paper. The new approach offers rational advantages over the leading neural algorithm - backpropagation. The comparative results obtained using receiver operating characteristic (ROC) analysis show that the ability of the convex set based method to infer knowledge is better than that of backpropagation, making it more suitable for use in real diagnostic systems.
AB - A novel convex set based neuro-fuzzy algorithm for classification of difficult-to-diagnose instances of breast cancer is described in this paper. The new approach offers rational advantages over the leading neural algorithm - backpropagation. The comparative results obtained using receiver operating characteristic (ROC) analysis show that the ability of the convex set based method to infer knowledge is better than that of backpropagation, making it more suitable for use in real diagnostic systems.
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M3 - Conference contribution
AN - SCOPUS:0033335220
SN - 0780356756
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 1132
BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PB - IEEE
T2 - Proceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
Y2 - 13 October 1999 through 16 October 1999
ER -