Online ISSN: 2515-8260

Keywords : Breast Cancer Survival Prediction


SURVEY ON VARIOUS PREDICTION MODELS FOR SURVIVAL OF BREAST CANCER PATIENTS USING WARM BOOT RANDOM FOREST CLASSIFIER

Vibin chandar; Dr. Krishnapriya . V

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 856-865

The rapid growth of genomics and proteomics in science has led to the
exponential development of information that requires a complex computational analysis to
find details. Review of statistical science or bioinformatics using knowledge mining centres
using bioinformatics to resolve a range of certifiable problems in the field of medical services.
Breast cancer malignant growth is the second most deadly form of disease that causes a
woman to die. Numerous experts have led to the early detection, visualisation and improved
management of malignancy in the breast cancer over the last 20 years, contributing to a
reduction in the rate of death. However the problem of malignancy in the breast
cancer remains concerning and requires further study in the territory of the development of
locations and forecasts other than treatment methods. This article explore the present
situation with the technique of estimating breast cancer disease status, which includes the
study on breast cancer malignancy, breast cancer, the prediction of the risk of malignant
growth, and the prediction of survival for breast cancer disease.