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- W2890250970 abstract "In this paper, we propose a novel method to classify Breast Lesions based on minute changes in the cell and nuclear features of the cell. It is important to note these changes as they play a significant role in diagnosis and the line of treatment by an oncologist. To overcome the problem of inter-observer variability the method of scoring is used to grade the lesions considered for the study. We have used the Modified Masood Score and designed an algorithm which classifies a given breast lesion into 6 classes namely Benign, Intermediate class-1,Intermediate class-2, Malignant class-1,Malignant class-2 and Malignant class-3. We have developed a sensitive model using the feed-forward neural network and Pattern Network to achieve the above objective. The Rank of the features is observed using ReliefF Algorithm." @default.
- W2890250970 created "2018-09-27" @default.
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- W2890250970 date "2018-08-13" @default.
- W2890250970 modified "2023-09-27" @default.
- W2890250970 title "Classification of Breast Lesions using Modified Masood Score and Neural Network" @default.
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- W2890250970 doi "https://doi.org/10.13005/bpj/1544" @default.
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