COMPARISON OF ARTIFICIAL NEURAL NETWORK AND PARAMETRIC REGRESSION MODELS IN SURVIVAL PREDICTION OF PATIENTS WITH GASTRIC CANCER

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.

BIGLARIAN A.; HAJIZADEH E.; KAZEMNEJAD A.

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

Journal Paper

Paper Information

Journal: Iranian Journal of Epidemiology Year:2010 | Volume:6 | Issue:3 Page(s): 22-27

Download Full-Text

Persian Verion

View:

814

Download:

Cites:

Information Journal Paper

Title

COMPARISON OF ARTIFICIAL NEURAL NETWORK AND PARAMETRIC REGRESSION MODELS IN SURVIVAL PREDICTION OF PATIENTS WITH GASTRIC CANCER

Author(s)

BIGLARIAN A. | HAJIZADEH E. | KAZEMNEJAD A. | Issue Writer Certificate

Keywords

SURVIVAL ANALYSISQ3

PREDICTIONQ3

PARAMETRIC MODELQ3

ARTIFICIAL NEURAL NETWORKQ2

GASTRIC CANCERQ2

Abstract

Background & Objective: Using PARAMETRIC MODELs is common approach in SURVIVAL ANALYSIS. In the recent years, ARTIFICIAL NEURAL NETWORK (ANN) models have increasingly used in survival PREDICTION. The aim of this study was to predict of survival rate of patients with GASTRIC CANCER by using a parametric regression and ANN models and compare these methods.Methods: We used the data of 436 GASTRIC CANCER patients from a cancer registry in Tehran in 2002-2007. All patients had a confirmed diagnosis. Data were randomly divided into two groups: training and testing (or validation) set. For analysis of data we used a PARAMETRIC MODEL (exponential, Weibull, normal, lognormal, logistic and log-logistic models) and a three layer ANN model. In order to compare of the PREDICTION of two models, we used the area under receiver operating characteristic (AUROC) curve, classification table and concordance index.Results: The PREDICTION accuracy of the ANN and the parametric (Weibull) models were 79.45% and 73.97% respectively. The AUROC for the ANN and the Weibull models were 0.815 and 0.748 respectively.Conclusions: The ANN had better PREDICTIONs than the Weibull model. Thus it is suggested to use of the ANN model survival PREDICTION in field of cancer.

Cites

No record.

References

Cite

APA: Copy

BIGLARIAN, A., HAJIZADEH, E., & KAZEMNEJAD, A.. (2010). COMPARISON OF ARTIFICIAL NEURAL NETWORK AND PARAMETRIC REGRESSION MODELS IN SURVIVAL PREDICTION OF PATIENTS WITH GASTRIC CANCER. IRANIAN JOURNAL OF EPIDEMIOLOGY, 6(3), 22-27. SID. https://sid.ir/paper/120580/en

Vancouver: Copy

BIGLARIAN A., HAJIZADEH E., KAZEMNEJAD A.. COMPARISON OF ARTIFICIAL NEURAL NETWORK AND PARAMETRIC REGRESSION MODELS IN SURVIVAL PREDICTION OF PATIENTS WITH GASTRIC CANCER. IRANIAN JOURNAL OF EPIDEMIOLOGY[Internet]. 2010;6(3):22-27. Available from: https://sid.ir/paper/120580/en

IEEE: Copy

A. BIGLARIAN, E. HAJIZADEH, and A. KAZEMNEJAD, “COMPARISON OF ARTIFICIAL NEURAL NETWORK AND PARAMETRIC REGRESSION MODELS IN SURVIVAL PREDICTION OF PATIENTS WITH GASTRIC CANCER,” IRANIAN JOURNAL OF EPIDEMIOLOGY, vol. 6, no. 3, pp. 22–27, 2010, [Online]. Available: https://sid.ir/paper/120580/en

Related Journal Papers