Open AccessA survey on predicting breast cancer survivability and its challenges
Author(s) -
Samaneh MiriRostami,
MohammadReza Parsaei,
Marzieh Ahmadzadeh
Publication year - 2019
Publication title -
journal of research in science, engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2693-8464
DOI - 10.24200/jrset.vol4iss03pp37-42
Subject(s) - survivability , breast cancer , health care , medicine , cancer , field (mathematics) , data mining , data science , computer science , intensive care medicine , computer network , mathematics , pure mathematics , economics , economic growth
Data mining is a powerful technology that can be used in all domains in order to detect hidden patterns from a large volume of data. A huge amount of medical data gives opportunities to health research community to extract new knowledge in different parts of medicine such as diagnosis, prognosis, and treatment by using data mining applications in order to improve the quality of patient care and reduce healthcare costs. Breast cancer is the most common cancer in women worldwide and it is the leading cause of death among women. Data mining can be used as a decision support system to predict survival of new patients. In this study, related works in the field of breast cancer survival prediction are reviewed and by compromising these works challenging issues are presented. Pages:37-42