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Published February 16, 2022 | Version v1
Journal article Open

RELATION BETWEEN POLYCYSTIC OVARY SYNDROME (PCOS) AND BULIMIA NERVOSA: CASE STUDY, RESPONSE SURFACE METHODOLOGY AND ARTIFICIAL INTELLIGENCE NEURAL NETWORKS (ANNS)

Description

Objective To examine the relation between polycystic ovary syndrome (PCOS) patients and bulimia represented in age, social status, national residency, chronic diseases, current medication, depression diagnosis and GAD diagnosis for the non-pregnant and non-breastfeeding patient.

Methods using dot plot curve to explore the relationship between patient parameter and bulimia nervosa disease (n=217), detecting significant variables by using linear regression analysis and make RSM relation equation between bulimia nervosa and other variables and to build the networks architecture between input covariables and output bulimia nervosa results multi-layer perceptron (MLP) neural networks.

Results indicated that about 8.8% of polycystic ovary syndrome (PCOS) patients suffering from bulimia nervosa. Age parameter is a significant variable for bulimia nervosa with an average age of 29.8947±6.4227. status and Diagnosis Date for PCOS patients are non-significant for bulimia nervosa investigations (p-value > 0.05).  All positive bulimia nervosa patients came from Buraydah and Unayzah residency. The results indicated that chronic diseases represented in Diabetes, thyroid disease and hypothyroidism have a relation with bulimia nervosa disease.  Also, Duphaston, thyroxin and diabetes medication have a relation with bulimia nervosa disease. About 26.3% of depressed patients and 73.7% of GAD patients have bulimia nervosa.

Conclusion RSM and ANN results indicated that the Age variable is the most significant variable for bulimia nervosa prediction followed by Residency, medication, Chronic Type and Depression Diagnosis with moderate significance. Finally, PCOs Diagnosis Date and GAD Diagnosis are not significant for bulimia nervosa disease.

Keywords: Bulimia nervosa; polycystic ovary syndrome; neural networks; chronic diseases; Age; Sex; Eating disorders

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14.Mansour Alharbi-Final bulimia nervosa PSOS.pdf

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