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Breast Cancer Survival Analysis and Mortality Prediction Under Different Treatment Combinations

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, a combination of breast cancer treatment procedures is considered, and its impact on breast cancer survival is precisely observed. Both statistical and neural network procedures are used to predict the breast cancer survival time. The results indicate that treatment procedures that use surgical options improve breast cancer survival. In the case of non-surgical options, hormone therapy appears to be the best. Additionally, the results suggest that radiation and chemotherapy combination lead to lower survival rates. The dataset used in this research had limited cases where the chemotherapy option was prescribed. Chemotherapy alone was a confounding cancer treatment option for non-node-positive cancer. For node-positive cancer cases, chemotherapy seems to work best where the surgery option is not considered or is viable. The experiments with neural networks show that neural networks can help predict the event of death, but these techniques could not accurately predict the length of survival.

Original languageEnglish (US)
Pages (from-to)125-136
Number of pages12
JournalJournal of Data Science and Intelligent Systems
Volume4
Issue number1
DOIs
StatePublished - Jan 28 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems

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