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

Ferdos Mohamadi Basatini; Zahra Chinipardaz; Maryam Seyed Tabib

Jentashapir Journal of Cellular and Molecular Biology

Official Journal of Ahvaz Jundishapur University of Medical Sciences

Current Issue All Issues In Press Accepted Manuscripts Search

Journal Information Editors & Boards Indexing and Listing Sources Journal Metrics Open Peer Review (OPR)Publication Ethics and Malpractice Statement Contact Us Support Reviewer and AE Registration Form

Authors Guide Submit Manuscript

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):

Ferdos Mohamadi Basatini^1,*,

Zahra Chinipardaz²,

Maryam Seyed Tabib³

1Instructor, Department of mathematic, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran

2Dental Student , School of Dentistry,Tehran University of Medical Sciences, Tehran, Iran

3Master Student of Biological Statistic, School of Public Health, Institute of Public Health Research, Tehran University of Medical Sciences, Tehran, Iran

Jentashapir Journal of Cellular and Molecular Biology:Vol. 4, issue 1; e94065

Published online:Feb 01, 2013

Article type:Research Article

Received:May 19, 2019

Accepted:Jul 29, 2012

How to Cite:Ferdos Mohamadi BasatiniZahra ChinipardazMaryam Seyed TabibDetermination 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 J Cell Mol Biol.4(1):e94065.

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

Keywords

Linear discrimination

Quadratic discrimination

Logistic discrimination

neural network discrimination

multilayer perceptron model

misclassification probability

Fulltext

The fulltext is available in PDF file.

References

1.
The references are available in PDF file.

comments