Machine Learning & Time Based Prediction of Breast Cancer Tumor Recurrence

Abstract

Breast cancer is one of the most deadly and commonly found cancers among women, taking thousands of lives each year. The proposed investigation is an attempt to use various machine-learning techniques to classify and predict the tumor. In the past various studies have successfully predicted the nature of the tumor to be benign or malignant and if the tumor will reoccur or not in the patient’s body. However, there is no previously developed time-based model. This study investigates how long the tumor will take to reappear in the patient’s body or the time patient will take for complete recovery. Various classification models such as Spectral clustering, DBSCAN, and k-means along with prediction models like Support Vector Machines, Decision trees, and Random forest are used. The extensive analysis can predict the time taken by the tumor to reoccur on the scale of 1 year. This timely prediction of cancer can help the patient to consult the doctor on time thus saving their life. Funding Information: The author has no funding source to declare. Declaration of Interests: The author declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.