DETERMINING OF THE FACTORS AFFECTING MORTALITY IN BURN PATIENTS USING A DECISION TREE DATA MINING ALGORITHM

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

AZIZI A.A.; ZAREI J.; NABOVATI E.; VAKILI ARKI H.; ABBASI E.; RAZAVI A.R.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download Full-Text

Persian Verion

View:

1,391

Download:

Cites:

Information Journal Paper

Title

DETERMINING OF THE FACTORS AFFECTING MORTALITY IN BURN PATIENTS USING A DECISION TREE DATA MINING ALGORITHM

Author(s)

Keywords

DATA MININGQ3

DECISION TREEQ2

BURNQ3

Abstract

Introduction: Using DATA MINING to develop prediction models from large amounts of data in medicine has become increasingly popular during the recent years. In this study, we intend to use a DECISION TREE DATA MINING algorithm in order to identify factors influencing mortality in BURN patients.Methods: The present retrospective descriptive study is based on BURNing patients’ records.Overall, the medical records of 4804 patients were scrutinized. The collected data were analyzed using statistical software (SPSS version 16), DATA MINING software (Clementine version 12), and CHAID algorithm.Results: The resulting model for predicting survival and mortality of BURNing patients included the percentage of Total BURN Surface Area (TBSA %), degree of BURN, length of stay, gender, and age of patients. Other variables including blood cultures, wound cultures, urine cultures, and the months of patient hospitalization had no effect on improving the efficiency of the model.Conclusion: The proposed model is valid and reliable due to its accuracy (approximately 95%). In fact, the results of this study, some of which are consistent with the results of other studies, can propose a comprehensive, accurate, and reliable local model for predicting mortality and survival of BURNing patients based on the mentioned variables. Thus, this local model can be used as an important criterion for evaluating the effective treatment of BURN patients.

Cites

No record.

References

No record.

Cite

APA: Copy

AZIZI, A.A., ZAREI, J., NABOVATI, E., VAKILI ARKI, H., ABBASI, E., & RAZAVI, A.R.. (2013). DETERMINING OF THE FACTORS AFFECTING MORTALITY IN BURN PATIENTS USING A DECISION TREE DATA MINING ALGORITHM. JOURNAL OF HEALTH ADMINISTRATION, 16(54), 34-45. SID. https://sid.ir/paper/130136/en

Vancouver: Copy

AZIZI A.A., ZAREI J., NABOVATI E., VAKILI ARKI H., ABBASI E., RAZAVI A.R.. DETERMINING OF THE FACTORS AFFECTING MORTALITY IN BURN PATIENTS USING A DECISION TREE DATA MINING ALGORITHM. JOURNAL OF HEALTH ADMINISTRATION[Internet]. 2013;16(54):34-45. Available from: https://sid.ir/paper/130136/en

IEEE: Copy

A.A. AZIZI, J. ZAREI, E. NABOVATI, H. VAKILI ARKI, E. ABBASI, and A.R. RAZAVI, “DETERMINING OF THE FACTORS AFFECTING MORTALITY IN BURN PATIENTS USING A DECISION TREE DATA MINING ALGORITHM,” JOURNAL OF HEALTH ADMINISTRATION, vol. 16, no. 54, pp. 34–45, 2013, [Online]. Available: https://sid.ir/paper/130136/en

Related Journal Papers