Vers la proposition d’une nouvelle approche basée sur les réseaux neuraux artificiels : application à la prédiction de la qualité de vie à travers la perception de la maladie chez les malades chroniques

Aim: Chronic illness affects many Algerians. It is possible to investigate the prediction ability of quality of life as a function to illness perception. 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 (SF-36V2) 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.