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    CMUR > China Medical University > Journal articles >  Item 310903500/28652
    Please use this identifier to cite or link to this item: http://ir.cmu.edu.tw/ir/handle/310903500/28652


    Title: Modifier effects on supercritical CO2 extraction efficiency of cephalotaxine from Cephalotaxus wilsoniana leaves
    Authors: Choi, YH;Kim, J;Kim, JY;Joung, SN;Yoo, KP;Chang, YS
    Contributors: 中國醫藥大學;Seoul Natl Univ, Coll Pharm, Kwanak Gu, Seoul 151742, South Korea;Sogang Univ, Dept Chem Engn, Seoul 121742, South Korea;China Med Coll, Taichung, Taiwan
    Date: 2000
    Issue Date: 2010-09-24 13:39:15 (UTC+8)
    Publisher: PHARMACEUTICAL SOCIETY KOREA
    Abstract: The purpose of this study was to evaluate the performance of neural network model self-organizing maps (SOM) in the classification of benign and malignant sonographic breast lesions. A total of 243 breast tumors (82 malignant and 161 benign) were retrospectively evaluated. When a sonogram was performed, the analog video signal was captured to obtain a digitized sonographic image. The physician selected the region of interest in the sonography, An SOM model using 24 autocorrelation texture features classified the tumor as benign or malignant. In the experiment, cases were sampled with k-fold cross-validation (k = 10) to evaluate the performance using receiver operating characteristic (ROC) curves,The ROC area index for the proposed SOM system is 0.9357 +/- 0.0152, the accuracy is 85.6%, the sensitivity is 97.6%, the specificity is 79.5%, the positive predictive value is 70.8%, and the negative predictive value is 98.5%. This computer-aided diagnosis system can provide a useful tool and its high negative predictive value could potentially help avert benign biopsies. (C) 2000 World Federation for Ultrasound in Medicine & Biology.
    Relation: ARCHIVES OF PHARMACAL RESEARCH 23(2):163-166
    Appears in Collections:[China Medical University] Journal articles

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