eng Oriental Scientific Publishing Company Biomedical and Pharmacology Journal 0974-6242 2018-09-21 11 3 1745 1748 10.13005/bpj/1544 21872 article Sonali Nandish Manoli 1 Anand Raj Ulle 1 N.M. Nandini 2 T.S. Rekha 2 Department of Information Science and Engineering, Sri Jayachamarajendra College of Engineering, Mysuru. Department of Pathology, JSS Medical College, Affiliated to JSS University Mysuru. 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. https://biomedpharmajournal.org/vol11no3/classification-of-breast-lesions-using-modified-masood-score-and-neural-network/ Computer Aided Diagnosis Feed-Forward Neural Network Machine Learning Modified Masood Score Neural Networks Pattern Network Performance Function and Training Function