(knowledge discovery) (health) (data mining)



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Transcription:

Magiran: Iranmedex, SID, Google Scholar, OVID, Scopus, PubMed (knowledge discovery) (health) (data mining) mostafadamroodi1992@yahoo.com

Mine Data (Knowledge discovery) Magiran, Iranmedex, data SID, Google Scholar, ovid, scopus, PubMed knowledge health, discovery minig (Data Mining)

(Wickramasinghe) Bayesian (Decisions Tree) DRG (Diagnosis Related Groups)

(Canlas) (Gorunescu) CAD (Computer Assisted Diagnosis) (Neural Networks) (Genetic Algorithms) ((Laboratory Information System (LIS)

ICD ObamaCare Arkansas Data Network (Invasive) Group Cooperative Health

33/25 / 92/41 (Randomization) (Maintain Anonymity) (query auditing) (Anthrax) (CRM) (Customer Relationship Management) (Preprocessing)

(Noise) Kdnugget

References 1- Rogers G, Joyner E. Mining Your Data for Healthcare Quality Improvement [Online]. 2011 [cited 2011 Aug 8]; Availablefrom: URL: http: //www2.sas.com/proceedings/ sugi22/emerging/paper139.pdf/ 2- Englebardt SP, Nelson R. Health care informatics: an interdisciplinary approach. Philadelphia: Mosby; 2002. pp125. 3- Koh HC, Tan G. Data mining applications in healthcare. J Health In Manage 2005; 19 (2): 64-72. 4- MPH, Assistant Professor of community Medicine Tehran University ofmedical Sciences 1387. 5- Medical Informatics, The internet Medicine ISSN 1436-9238, Print /ISSN 1464-5238online c 2000 Taylor& Francis Ltd. Available from: http: //www.tandf.co.uk /journals. 6- Hassanzadeh M, Razavi Ebrahimi SL. Comparison 9- Obenshain MK. Application of data mining techniques to healthcare data. Infect Control. HospEpidemiol. 2004;25 (8): 690-5. 12- Wickramasinghe N, Gupta JN, Sharma SK. Creating Knowledge-Based Healthcare Organizations. Hershey: IdeaGroup Inc (IGI). 2005. 7- Esmaeili M. Concepts & Techniques datamining, Tehran: Niasedanesh Publisher;1391. 16- Hian ChyeKoh, Gerald Tan. Data Mining Applications in Healthcare. Journal of Healthcare Information Management. Vol.19, No.2. 17- http: //www.tamin.ir/news/item.

Evaluation of Data Mining Applications in the Health System Leila Gholamhosseini 1, Mostafa Damroodi* 1 Abstract Introduction: Extensive amounts of data stored in medical databases require the development of specialized tools for accessing the data, data analysis, knowledge discovery, and the effective use of the data. Data mining is one of the most important methods. The article sketches the used Data Mining techniques, and illustrates their applicability to medical diagnostic and prognostic problems. Materials and Methods: The current study were searched English and Persian databases including Magiran, Iranmedex, SID, Google Scholar, OVID, Scopus, and PubMed by using keywords such as Data Mining, Knowledge Discovery and Health. Related articles were published and assessed during 1998-2013. Findings: models and association rules in them where other statistical analysis cannot do that. The medical science is one of sciences that need to use of these tools for analyzing the large amount of data and creating predictive model with the new computation ways. In medical sciences, discovery and early diagnosis of the diseases can restrict the fatal diseases such as cancer and they save a people s life. This research is shown that the data mining prediction provide necessary tools for the researcher and the physician to improve in the prevention of disease, diagnosis ways and their treatment programs. Discussion and Conclusion: Nowadays, in the medical sciences, data collection of different diseases is very important. Recent development related to information technology & software has helped to have the better survey from producing massive data and could search the hidden knowledge in the data and create a new science by using different sciences including statistics, computers, and machine learning, and etc. Keywords: data mining, health, knowledge discovery 1- (*Corresponding author) Department of Health Information Technology, Faculty of Paramedicine, AjA University of Medical Sciences, Tehran, Iran. E-mail: mostafadamroodi1992@yahoo.com

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