THE DIAGNOSIS OF THYROID DISEASES USING COMBINATION OF NEURAL NETWORKS THROUGH HIERARCHICAL METHOD

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.

ZABBAH IMAN; YASREBI NAEINI SEYED EHSAN; RAMAZANPOOR ZAHRA; SAHRAGARD KHADIJE

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

Journal Paper

Paper Information

Journal: Journal of Health and Biomedical Informatics Year:2017 | Volume:4 | Issue:1 Page(s): 21-31

Download Full-Text

Persian Verion

View:

1,668

Download:

Cites:

Information Journal Paper

Title

THE DIAGNOSIS OF THYROID DISEASES USING COMBINATION OF NEURAL NETWORKS THROUGH HIERARCHICAL METHOD

Author(s)

ZABBAH IMAN | YASREBI NAEINI SEYED EHSAN | RAMAZANPOOR ZAHRA | SAHRAGARD KHADIJE | Issue Writer Certificate

Keywords

ARTIFICIAL NEURAL NETWORKQ1

MLP NETWORKQ2

COMBINATION OF NEURAL NETWORKSQ2

THYROID DIAGNOSISQ2

Abstract

Introduction: Problems in thyroid gland are more common than in other glands of human body, and if they are not diagnosed early, thyroid storm or myxedema coma is likely to happen that might lead to death; therefore, on-time diagnosis of thyroid disorders (Hypothyroidism or hyperthyroidism) based on Laboratory and clinical tests is necessary. The main object of this research was to present a model based on data mining techniques that is capable of predicting thyroid diseases.Methods: This study was a descriptive-analytic study and its database included 7200 independent records based on 21 risk factors derived from UCI data reference. From all records, 70% were used for training and 30% for testing. First, neural networks performance was reviewed in order to diagnose thyroid diseases, and then an algorithm for COMBINATION OF NEURAL NETWORKS through hierarchical method was presented.Results: After modeling and comparing the generated models and recording the results, accuracies of predicting thyroid disorders using neural network and hierarchical method were found to be 96.6% and 100% respectively.Conclusion: Reducing misdiagnosis of thyroid diseases has always been one of the most important aims of researchers. Using methods based on data mining can decrease these errors. This study showed that using COMBINATION OF NEURAL NETWORKS through hierarchical method improves diagnosis accuracy.

Cites

Detection of Knee Osteoarthritis Using Image Segmentation and Artificial Neural Networks

References

Cite

APA: Copy

ZABBAH, IMAN, YASREBI NAEINI, SEYED EHSAN, RAMAZANPOOR, ZAHRA, & SAHRAGARD, KHADIJE. (2017). THE DIAGNOSIS OF THYROID DISEASES USING COMBINATION OF NEURAL NETWORKS THROUGH HIERARCHICAL METHOD. JOURNAL OF HEALTH AND BIOMEDICAL INFORMATICS, 4(1), 21-31. SID. https://sid.ir/paper/258916/en

Vancouver: Copy

ZABBAH IMAN, YASREBI NAEINI SEYED EHSAN, RAMAZANPOOR ZAHRA, SAHRAGARD KHADIJE. THE DIAGNOSIS OF THYROID DISEASES USING COMBINATION OF NEURAL NETWORKS THROUGH HIERARCHICAL METHOD. JOURNAL OF HEALTH AND BIOMEDICAL INFORMATICS[Internet]. 2017;4(1):21-31. Available from: https://sid.ir/paper/258916/en

IEEE: Copy

IMAN ZABBAH, SEYED EHSAN YASREBI NAEINI, ZAHRA RAMAZANPOOR, and KHADIJE SAHRAGARD, “THE DIAGNOSIS OF THYROID DISEASES USING COMBINATION OF NEURAL NETWORKS THROUGH HIERARCHICAL METHOD,” JOURNAL OF HEALTH AND BIOMEDICAL INFORMATICS, vol. 4, no. 1, pp. 21–31, 2017, [Online]. Available: https://sid.ir/paper/258916/en

Related Journal Papers