• Register
  • Login

European Journal of Molecular & Clinical Medicine

  • Home
  • Browse
    • Current Issue
    • By Issue
    • By Subject
    • Keyword Index
    • Author Index
    • Indexing Databases XML
  • Journal Info
    • About Journal
    • Aims and Scope
    • Editorial Board
    • Publication Ethics
    • Indexing and Abstracting
    • Peer Review Process
    • News
  • Guide for Authors
  • Submit Manuscript
  • Contact Us
Advanced Search

Notice

As part of Open Journals’ initiatives, we create website for scholarly open access journals. If you are responsible for this journal and would like to know more about how to use the editorial system, please visit our website at https://ejournalplus.com or
send us an email to info@ejournalplus.com

We will contact you soon

  1. Home
  2. Volume 7, Issue 9
  3. Authors

Online ISSN: 2515-8260

Volume7, Issue9

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

  • Show Article
  • Download
  • Cite
  • Statistics
  • Share

Abstract

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.
Keywords:
    Breast Cancer (BC) Breast Cancer Survival Prediction Breast Cancer Risk Prediction Random Forest Decision Tree AdaBoost
  • PDF (242 K)
  • XML
(2020). SURVEY ON VARIOUS PREDICTION MODELS FOR SURVIVAL OF BREAST CANCER PATIENTS USING WARM BOOT RANDOM FOREST CLASSIFIER. European Journal of Molecular & Clinical Medicine, 7(9), 856-865.
Vibin chandar; Dr. Krishnapriya . V. "SURVEY ON VARIOUS PREDICTION MODELS FOR SURVIVAL OF BREAST CANCER PATIENTS USING WARM BOOT RANDOM FOREST CLASSIFIER". European Journal of Molecular & Clinical Medicine, 7, 9, 2020, 856-865.
(2020). 'SURVEY ON VARIOUS PREDICTION MODELS FOR SURVIVAL OF BREAST CANCER PATIENTS USING WARM BOOT RANDOM FOREST CLASSIFIER', European Journal of Molecular & Clinical Medicine, 7(9), pp. 856-865.
SURVEY ON VARIOUS PREDICTION MODELS FOR SURVIVAL OF BREAST CANCER PATIENTS USING WARM BOOT RANDOM FOREST CLASSIFIER. European Journal of Molecular & Clinical Medicine, 2020; 7(9): 856-865.
  • RIS
  • EndNote
  • BibTeX
  • APA
  • MLA
  • Harvard
  • Vancouver
  • Article View: 265
  • PDF Download: 287
  • LinkedIn
  • Twitter
  • Facebook
  • Google
  • Telegram
Journal Information

Publisher:

Email:  editor.ejmcm21@gmail.com

  • Home
  • Glossary
  • News
  • Aims and Scope
  • Privacy Policy
  • Sitemap

 

For Special Issue Proposal : editor.ejmcm21@gmail.com

This journal is licensed under a Creative Commons Attribution 4.0 International (CC-BY 4.0)

Powered by eJournalPlus