DETERMINATION OF THYROID GLAND STATE IN REFERRALS FROM AHVAZ UNIVERSITY JAH AD LABORATORY: USING MULTILAYER PERCEPTRON NEURAL NETWORK DISCRIMINATION IN COMPARING WITH CLASSICAL DISCRIMINATION METHODS

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MOHAMADI BASATINI FERDOS; CHINIPARDAZ ZAHRA; SEYED TABIB MARYAM

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Paper Information

Journal: Jentashapir Journal of Cellular and Molecular Biology Year:2013 | Volume:4 | Issue:1 Page(s): 11-21

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Title

DETERMINATION OF THYROID GLAND STATE IN REFERRALS FROM AHVAZ UNIVERSITY JAH AD LABORATORY: USING MULTILAYER PERCEPTRON NEURAL NETWORK DISCRIMINATION IN COMPARING WITH CLASSICAL DISCRIMINATION METHODS

Author(s)

MOHAMADI BASATINI FERDOS | CHINIPARDAZ ZAHRA | SEYED TABIB MARYAM | Issue Writer Certificate

Keywords

LINEAR DISCRIMINATIONQ3

QUADRATIC DISCRIMINATIONQ3

LOGISTIC DISCRIMINATIONQ3

NEURAL NETWORK DISCRIMINATIONQ3

MULTILAYER PERCEPTRON MODELQ3

MISCLASSIFICATION PROBABILITYQ3

Abstract

Background: One of the main objects in medical science is diagnosis the diseases and classification the patients to different classes. Consequently according to the above the patients that set in one classes should have maximum similarity with each other. Discrimination and classification analysis have been frequently used in medical data for diagnosis and prognostic of the disease. The wrong in the medical diagnosis is very important, hence the decrease of wrong diagnosis in the discrimination methods are to consider always. Different methods have been used for classification and discrimination of medical data for years. The intention of this research is determination the state of tiroid gland using linear, quadratic and LOGISTIC DISCRIMINATION in camper with the most up-to-date method NEURAL NETWORK DISCRIMINATION.Methods: A total of 225 patients’ data from Jahad university laboratory has analyzed. The obtained data correlated to November 2005. Using spluss/2000 software the collected information proceeds within four methods.Results: The consequences revealed that LINEAR DISCRIMINATION misdiagnosis with training set and test set were 0.14 and 0.213 respectively. However these figures considered by QUADRATIC DISCRIMINATION were 0.053 and 0.106 correspondingly. The obtained records through LOGISTIC DISCRIMINATION for both training set and test set was 0.026 and 0.026. Yet these facts for NEURAL NETWORK DISCRIMINATION recorded in 0.02 and 0.013 likewise.Conclusion: The NEURAL NETWORK DISCRIMINATION had possibly superior decrease in wrong diagnosis and with notice to the fact that the method need a very fewer statistical assumption, this method is proposed.

Cites

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

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APA: Copy

MOHAMADI BASATINI, FERDOS, CHINIPARDAZ, ZAHRA, & SEYED TABIB, MARYAM. (2013). DETERMINATION OF THYROID GLAND STATE IN REFERRALS FROM AHVAZ UNIVERSITY JAH AD LABORATORY: USING MULTILAYER PERCEPTRON NEURAL NETWORK DISCRIMINATION IN COMPARING WITH CLASSICAL DISCRIMINATION METHODS. JENTASHAPIR JOURNAL OF CELLULAR AND MOLECULAR BIOLOGY (JENTASHAPIR JOURNAL OF HEALTH RESEARCH), 4(1), 11-21. SID. https://sid.ir/paper/205763/en

Vancouver: Copy

MOHAMADI BASATINI FERDOS, CHINIPARDAZ ZAHRA, SEYED TABIB MARYAM. DETERMINATION OF THYROID GLAND STATE IN REFERRALS FROM AHVAZ UNIVERSITY JAH AD LABORATORY: USING MULTILAYER PERCEPTRON NEURAL NETWORK DISCRIMINATION IN COMPARING WITH CLASSICAL DISCRIMINATION METHODS. JENTASHAPIR JOURNAL OF CELLULAR AND MOLECULAR BIOLOGY (JENTASHAPIR JOURNAL OF HEALTH RESEARCH)[Internet]. 2013;4(1):11-21. Available from: https://sid.ir/paper/205763/en

IEEE: Copy

FERDOS MOHAMADI BASATINI, ZAHRA CHINIPARDAZ, and MARYAM SEYED TABIB, “DETERMINATION OF THYROID GLAND STATE IN REFERRALS FROM AHVAZ UNIVERSITY JAH AD LABORATORY: USING MULTILAYER PERCEPTRON NEURAL NETWORK DISCRIMINATION IN COMPARING WITH CLASSICAL DISCRIMINATION METHODS,” JENTASHAPIR JOURNAL OF CELLULAR AND MOLECULAR BIOLOGY (JENTASHAPIR JOURNAL OF HEALTH RESEARCH), vol. 4, no. 1, pp. 11–21, 2013, [Online]. Available: https://sid.ir/paper/205763/en

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