Artificial intelligence and stochastic processbased analysis of human psychiatric disorders

This paper contains an analysis and comparison of different classifiers on different datasetsof Psychiatric Disorders- Personality Disorder, Depression, Anxiety, Schizophreniaand Alzheimer's disease. Psychiatric disorders are also referred to as mental disorders,abnormalities of the mind that result in persistent behavior which can seriously cause dayto day function and life. Stochastic in AI refers to if there is any uncertainty or randomnessinvolved in results and are used during optimization; Using this process also helps toprovide precise results. The study of stochastic process in AI uses mathematical knowledgeand techniques from probability, set theory, calculus, linear algebra and mathematicalanalysis like Fourier analysis, real analysis, and functional analysis. this technique is usedto construct neural network for making artificial intelligent mode for processing andminimizing human effort. This paper contains classifiers like SVM, MLP, LR, KNN, DT,and RF. Several types of attributes are used and have been trained by Weka tool, MATLAB,and Python. The results show that the SVM classifier showed the best performance for allthe attributes and disorders researched in this paper.