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  1. Ngah, U.K., Aziz, S.A., Aziz, M.E., Murad, M., Mahdi, N.M.N., Shakaff, A.Y.M., et al.
    ASM Science Journal, 2008;2(1):1-11.
    MyJurnal
    The incidences of breast cancer have been rising at an alarming rate. Mass breast screening programmes involving mammography and ultrasound in certain parts of the world have also proven their benefits in early detection. However, radiologists may be confronted with increased workload. An attempt has been made in this paper to rectify part of the problems faced in this area. Expert systems based on the interpretation of mammographic and ultrasound images for classifying patient cases could be utilized by doctors (expert and non-expert) in screening. These softwares consist of MAMMEX (for mammogram) and SOUNDEX (for breast ultrasound) could be used to deduce cases according to Breast Imaging Recording and Data System (BI-RADS), based on patients’ history, physical and clinical assessment, mammograms and breast ultrasound images. A total of 179 retrospective cases from the Radiology Department, hospital of the University of Science Malaysia, Kubang Kerian, Kelantan were used in this study. A receiver operating characteristic (ROC) curve analysis was implemented, based on the usage of a two-class forced choice of classifying suspicious and malignant findings as positive with normal, benign and probably benign classified as negative. Results yielded an area under the curve (AUC) of 0.997 with the least standard error value of 0.003 for MAMMEX while an AUC of 0.996 with the least standard error of 0.004 was accomplished for SOUNDEX. A system which very closely simulated radiologists was also successfully developed in this study. The ROC curve analysis indicated that the expert systems developed were of high performance and reliability.
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