Understanding medical text related to breast cancer: A review

Noha Ali*, Eslam Amer, Hala Zayed

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Breast Cancer is a harmful disease that has caused millions of women deaths. There are a huge number of publications on breast cancer research which offers a good source of information. Identifying breast cancer biomarkers is not a trivial task. There are many approaches used to identify and extract the needed information more efficiently from structured/unstructured text, uncover relationships and hidden rules from the huge amount of information such as text mining, machine learning and data mining. This paper reviews some of research literature on breast cancer using these approaches.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Advanced Intelligent Systems and Informatics 2017
EditorsMohamed F. Tolba, Tarek Gaber, Khaled Shaalan, Aboul Ella Hassanien
PublisherSpringer
Pages280-288
Number of pages9
ISBN (Electronic)9783319648613
ISBN (Print)9783319648606
DOIs
Publication statusPublished - 31 Aug 2017
Event3rd International Conference on Advanced Intelligent Systems and Informatics, AISI 2017 - Cairo, Egypt
Duration: 9 Sept 201711 Sept 2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume639
ISSN (Print)2194-5357

Conference

Conference3rd International Conference on Advanced Intelligent Systems and Informatics, AISI 2017
Country/TerritoryEgypt
CityCairo
Period9/09/1711/09/17

Keywords

  • Breast cancer
  • Data mining
  • NLP
  • Text mining

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