Using machine learning techniques to investigate a discreet type mathematical model of psychological mental disease

Recently machine learning techniques have attracted much attention. Artificial intelligence (AI) techniques using deep neural networks (DNNs) have given proper attention by researchers in the last few years. Various problems have been studied by using the mentioned tools. A mathematical model for psychological mental disorder with harmonic mean type incidence rate is formulated. World wide, the psychological diseases have produced very harmful impact on human life. For instance anxiety and depression are common every where and large numbers of people are suffering from such situation. Since, mathematical models are the best tools to investigate such diseases for further comprehensive analysis which help therapists and medical experts to cure their patients. We use the discrete type difference operator of fractional order to analyze the considered model and compute its fundamental components like equilibrium points, positivity boundedness and reproductive number. Also, the qualitative theory for the existence of solution has been deduced. Numerical interpretations against various fractional orders are illustrated to demonstrate the results graphically.