Data Mining, an Approach for Developing the Health Domain

Nowadays, data mining as the process of arrangement and classifications of voluminous data is one of the most important technics for studying and analyzing data in different organizations and domains. Data mining is among technological improvements towards data managing. Also, the wide use of information systems and databases has converted its merging with traditional methods into a necessity. Due to the existence of the large datasets in health-care organizations, data mining process has become necessary towards the automatic summarization of data and the extraction of the stored information and detection of the pattern from data. As nowadays the wide volume of data is daily obtained during care and treatment processes, analyzing them in order to discover the patterns and new science that can be resulted to upgrade health has been extremely inconspicuous. Therefore, the purpose of the present research is studying strategies and technics of data mining as one of the most important approaches in the development of health domains.

[1]  Hsinchun Chen,et al.  Medical Informatics: Knowledge Management and Data Mining in Biomedicine (Operations Research/Computer Science Interfaces) , 2005 .

[2]  Ruey-Shun Chen,et al.  Using data mining technology to solve classification problems: A case study of campus digital library , 2006, Electron. Libr..

[3]  Alex Berson,et al.  Building Data Mining Applications for CRM , 1999 .

[4]  Lingyun Zhu,et al.  [Introduction to medical data mining]. , 2003, Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi.

[5]  Mary K Obenshain.  Application of Data Mining Techniques to Healthcare Data , 2004, Infection Control & Hospital Epidemiology.

[6]  Daniel T. Larose,et al.  Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .

[7]  W. Seifert,et al.  Congressional Research Service Report RL31798 Data Mining and Homeland Security: An Overview , 2009 .

[8]  Ernestina Menasalvas Ruiz,et al.  Toward data mining engineering: A software engineering approach , 2009, Inf. Syst..

[9]  K.J. Cios,et al.  From the guest editor medical data mining and knowledge discovery , 2000, IEEE Engineering in Medicine and Biology Magazine.

[10]  Rafael Berlanga Llavori,et al.  Topic discovery based on text mining techniques , 2007, Inf. Process. Manag..

[11]  Chris Clifton,et al.  Emerging standards for data mining , 2001, Comput. Stand. Interfaces.

[12]  Kyle Banerjee,et al.  Is data mining right for your library , 1998 .

[13]  S. Englebardt,et al.  Health care informatics : an interdisciplinary approach , 2002 .

[14]  Kim Guenther.  Applying Data Mining Principles to Library Data Collection. , 2000 .

[15]  Chao-Ton Su,et al.  A Kano-CKM model for customer knowledge discovery , 2006 .

[16]  M. Sepehri,et al.  A DATA MINING BASED MODEL FOR SELECTING TYPE OF TREATMENT FOR KIDNEY STONE PATIENTS , 2009 .

[17]  John P. Glaser,et al.  Managing Health Care Information Systems: A Practical Approach for Health Care Executives , 2005 .

[18]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[19]  Jeffrey W. Seifert,et al.  Data Mining: An Overview , 2004 .

[20]  Rajeev K. Bali,et al.  Clinical knowledge management : opportunities and challenges , 2005 .

[21]  Michael J. A. Berry,et al.  Data mining techniques - for marketing, sales, and customer support , 1997, Wiley computer publishing.

[22]  Jan Rauch,et al.  Data Mining and Medical Knowledge Management: Cases and Applications , 2009 .

[23]  Joseph K. H. Tan.  Medical informatics : concepts, methodologies, tools, and applications , 2009 .