FUZZY CLUSTERING BASED BAYESIAN FRAMEWORK TO PREDICT MENTAL HEALTH PROBLEMS AMONG CHILDREN

ICTACT Journal on Soft Computing ( Volume: 7 , Issue: 3 )

Abstract

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According to World Health Organization, 10-20% of children and adolescents all over the world are experiencing mental disorders. Correct diagnosis of mental disorders at an early stage improves the quality of life of children and avoids complicated problems. Various expert systems using artificial intelligence techniques have been developed for diagnosing mental disorders like Schizophrenia, Depression, Dementia, etc. This study focuses on predicting basic mental health problems of children, like Attention problem, Anxiety problem, Developmental delay, Attention Deficit Hyperactivity Disorder (ADHD), Pervasive Developmental Disorder(PDD), etc. using the machine learning techniques, Bayesian Networks and Fuzzy clustering.
The focus of the article is on learning the Bayesian network structure using a novel Fuzzy Clustering Based Bayesian network structure learning framework. The performance of the proposed framework was compared with the other existing algorithms and the experimental results have shown that the proposed framework performs better than the earlier algorithms.

Authors

M R Sumathi1, B Poorna2
Bharathiar University, India1, Shri Shankarlal Sundarbai Shasun Jain College for Women, India2

Keywords

Fuzzy Clustering, Bayesian Network, Structure Learning, Prediction

Published By
ICTACT
Published In
ICTACT Journal on Soft Computing
( Volume: 7 , Issue: 3 )
Date of Publication
April 2017
Pages
1452-1458

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