Batna Journal of Medical Sciences
Volume 3, Numéro 2, Pages 98-103
2016-12-31
Towards The Proposition Of A New Approach Based On Artificial Neural Networks : Application To Quality Of Life Prediction Through Illness Perception With Chronic Illness Patients
Authors : Aberkane Salah .
Abstract
Aim: Chronic illness affects many Algerians. It is possible to investigate the prediction ability of quality of life as a function of illness perception. In In this study, we focus the assessment of the influence of patient’s chronic health condition perception on the quality of life using an Artificial Neural Network (ANN) based approach) The Radial Basis Function). Method: Three hundred and sixteen participants (16- 79 years old) from Arris and Batna regions in Algeria have completed the Revised Illness Questionnaire and Short Form 36 Health Survey Version 2.0 (SF36V2) scale. Results: The correlations between the predicted and real values of quality-of-life dimensions were 0.34 to 0.43. The importance of the illness length is visible in the plots for perceived quality of life (Physical Functioning, Role Physical), whereas other quality of life dimensions (Vitality and Mental Health) are less visible. Conclusion: The artificial neural networks has proved the diagnosis results to be correct and could be useful for assessment of the influence of patients’ chronic health condition perception on the quality of life.
Keywords
Illness perception; Quality of life; Artificial Neural Networks (ANN); The Radial Basis Function (RBF).
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