Genetic analysis for breast cancer prediction and diagnosis

Breast cancer signifies one of the diseases which contributes to a huge number of deaths each year. It is the most usual kind of cancer and also one of the main reasons for women's deaths globally. In the medical domain, data mining methods and Artificial Intelligence algorithms are used in early prognosis to make decisions. In this paper, we have highlighted the root cause of Breast cancer with the imbalance of Genomes. Also, we have described some of the existing predictions using various algorithms for breast cancer data. Our proposed architecture involves a combination of Artificial Intelligence algorithms and genetic algorithms as we have focused not only on the prediction of Breast cancer but also, included the genetic algorithm for genome sequencing promptly to the identified people, to avoid the stages of Breast cancer with respect to the time of identification. We have predicted the breast cancer genome dataset using some machine learning algorithms, where the Support Vector Machine algorithm gives a prediction accuracy of 61.55%. We are researching and working on the results for identifying the most accurate genetic algorithm to complete the design of a cost-effective model for genome sequencing.