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数据挖掘与医学领域:乳腺癌的诊断、治疗、预后及挑战

Data mining and medical world: breast cancers' diagnosis, treatment, prognosis and challenges.

作者信息

Oskouei Rozita Jamili, Kor Nasroallah Moradi, Maleki Saeid Abbasi

机构信息

Department of Computer Science and Information Technology, Mahdishahr Branch, Islamic Azad University Mahdishahr, Iran.

Research Center of Physiology, Faculty of Medicine, Semnan University of Medical SciencesSemnan, Iran; Student Research Committee, Faculty of Medicine, Semnan University of Medical SciencesSemnan, Iran.

出版信息

Am J Cancer Res. 2017 Mar 1;7(3):610-627. eCollection 2017.

Abstract

The amount of data in electronic and real world is constantly on the rise. Therefore, extracting useful knowledge from the total available data is very important and time consuming task. Data mining has various techniques for extracting valuable information or knowledge from data. These techniques are applicable for all data that are collected inall fields of science. Several research investigations are published about applications of data mining in various fields of sciences such as defense, banking, insurances, education, telecommunications, medicine and etc. This investigation attempts to provide a comprehensive survey about applications of data mining techniques in breast cancer diagnosis, treatment & prognosis till now. Further, the main challenges in these area is presented in this investigation. Since several research studies currently are going on in this issues, therefore, it is necessary to have a complete survey about all researches which are completed up to now, along with the results of those studies and important challenges which are currently exist in this area for helping young researchers and presenting to them the main problems that are still exist in this area.

摘要

电子领域和现实世界中的数据量一直在不断增加。因此,从所有可用数据中提取有用的知识是一项非常重要且耗时的任务。数据挖掘有多种从数据中提取有价值信息或知识的技术。这些技术适用于在所有科学领域收集的所有数据。关于数据挖掘在诸如国防、银行、保险、教育、电信、医学等各个科学领域的应用,已经发表了多项研究调查。本研究试图对迄今为止数据挖掘技术在乳腺癌诊断、治疗和预后方面的应用进行全面综述。此外,本研究还介绍了这些领域的主要挑战。由于目前有几项关于这个问题的研究正在进行,因此,有必要对迄今为止已完成的所有研究进行全面综述,包括这些研究的结果以及该领域目前存在的重要挑战,以帮助年轻研究人员,并向他们展示该领域仍然存在的主要问题。

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