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Data Mining In Health Care

578 Words3 Pages

In an information technology driven society, knowledge is one of the significant assets for any organization and its use in health care sector is one such application. Efficient use of database systems, data warehousing and knowledge management technologies can help in decision making in health care. In decision making data mining plays a major role and data mining is defined as the process of determining previously unknown and potentially useful information about data. Data mining technology helps to track original and hidden patterns in data. The so determined data information will help improve quality of service by stakeholders as health care data is massive. Health care organizations must have ability to analyse and interpret the data. …show more content…

In rule based technique the system conducts if-then analysis. IF-THEN predictive rules are used frequently in data mining. In the health care system, it can be applied as …show more content…

Healthcare data mining is restricted by the availability of data, because necessary inputs for data mining exist in different locations and systems such as laboratory, data banks of hospitals, clinics etc. Further, as large volume of data is involved there is a need to make a data secure and safe from being getting corrupted or inconsistent across the platforms. Moreover, doctors, physicians, healthcare executives are to be convinced about the usefulness of data mining as this is an emerging field and acceptance might take time among health care professionals. Thus, to make the data mining successful cooperation and collaboration of all stakeholders is needed.

REFERENCES
1. Kaur, H., & Wasan, S. K. (2006). Empirical Study on Applications of Data Mining Techniques in Healthcare. Journal of Computer Science, 2(2), 194-200. doi:10.3844/jcssp.2006.194.200
(https://pdfs.semanticscholar.org/9c64/b5bf41f274100d7b8d47792da5bedb0ee7f8.pdf)
2. Koh , H.C., Tan, G. , Data Mining Applications in Healthcare, Journal of Healthcare Information Management — Vol.19, No.2

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