Presenting a Smart Model for Distinguishing Patients With Thyroid Diseases From Healthy People by Combining Particle Swarm Optimization Algorithm and Artificial Neural Network

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Hosseinpoor Mohammadjavad

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Journal Paper

Paper Information

Journal: Journal of Modern Medical Information Science Year:2023 | Volume: | Issue: Page(s): 222-233

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Information Journal Paper

Title

Presenting a Smart Model for Distinguishing Patients With Thyroid Diseases From Healthy People by Combining Particle Swarm Optimization Algorithm and Artificial Neural Network

Author(s)

Hosseinpoor Mohammadjavad | Issue Writer Certificate

Keywords

PredictionQ4

Thyroid diseaseQ4

Disease diagnosisQ4

Evolutionary algorithmQ4

Learning modelQ4

Abstract

2Objective Thyroid diseases are common disorders worldwide. The timely diagnosis and control of this disease can prevent its progression and reduce associated complications. This study proposes a novel hybrid method by combining particle swarm optimization (PSO) algorithm and artificial neural network (ANN) for the timely detection of thyroid disorders. Methods This is an applied survey study, conducted in 2022. In this study, the target population consisted of the data of 400 patients referred to Imam Reza Hospital in Lar County, Iran from 2021 to 2022 which were collected by field study. Among them, 300 had Thyroid disease and 100 were healthy. MATLAB software was used for implementing the proposed Learning model and analyzing the results. Results The regression coefficient of the proposed model in there modes of training, validation, and testing were 0.98, 0.97, and 0.95, respectively. The area under the ROC curve was 0.98, the error rate was 0.004, and the overall accuracy was 96%. Conclusion The proposed model can distinguish patients with Thyroid disease from healthy individuals with acceptable accuracy and low errors. This model can be used as a useful tool in predicting Thyroid diseases.

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