Breast Cancer Recognition Using Integrated Lasso Based Artificial Intelligence Approach
D. Balakrishnan, Umasree Mariappan, G Sreedevi, Nanditha Alagusundar, P. Abhishekh, V Sowjyasree · 2023
Breast cancer is the most found disease in the women's which spreads throughout the body if it doesn't concentrated well. There are more technologies has been introduced earlier for the detection of breast cancer. However there is no efficient technology to find the breast cancer in the severe stage and reaches distant metastasis. In the existing work, it is done by using the various machine learning algorithms, which will predict the disease occurrence by learning the various genes associated with them by Analysing the gene structure. However those techniques are complex in nature and cannot predict the diseases in the accurate way due to its varying characteristics. These issues are resolved in the proposed methodology by introducing the method namely Lasso based Artificial Intelligence Approach (LAIA) for breast cancer Recognition which is in the distant metastasis stage. In the proposed research work, input datasets were pre-processed first which is then given as input to the LAIA method which can detect the disease more accurately. The analysis were done in the matlab simulation environment and then the comparison has been made against the various existing techniques such as adaboost and XGBoost algorithms. The metrics considered for the evaluation are accuracy, F1 Score, Positive Predictive Value, Sensitivity and AUC values. The comparison analysis proved that the proposed methodology attains better performance improvement than the existing methodologies.