A comparative study for improved hospital-based cancer registry for early stage prediction of breast cancer with highest accuracy

Abstract

Breast cancer prediction has always been a challenge and machine-learning algorithms provide great assistance in this regard. This research paper precisely reports efforts in identification and development of appropriate algorithms that can predict breast cancer with high accuracy. The research undertaken is based on rigorous analysis of data collected from Bikaner, Rajasthan, India and its quality and features in comparison to the standard SEER dataset. The results confirm the applicability of classification algorithms like support vector machine in building a machine-learning model for accurate prediction of early stage breast cancer. Finally, as a highlighting contribution, a prediction model, which resulted in prediction of cancer with 99% accuracy on the data collected from patients in Bikaner, Rajasthan, India has been presented. This model will help to improve the National Cancer Registry Program and hospital based cancer registry systems.