Psychological Consultation and Health Analysis Method for Artificial Intelligence Multidecision Support

Abstract

With the increase in market economy and life competition, mental health problems are particularly prominent in today’s society. This is also an important reason for the sudden increase in extreme events. The frequent occurrence of violent incidents and depressive incidents is mainly caused by major problems in mental health. They accumulate greater pressure in life or study, which can easily lead to mental health problems. However, mental health problems are difficult to detect up front. When the mental health problem is more serious, they will seek a psychological counselor or a way to release stress to solve the mental health problem. Only a small number of people will take extreme measures, which will cause social or family losses. Artificial intelligence methods have better advantages in dealing with nonlinear relationships of features. This study uses a convolutional neural network (CNN) and long short-term memory (LSTM) methods in artificial intelligence methods to study the characteristics of psychological counseling and health. The research results show that CNN and LSTM methods can accurately predict the characteristics of psychological counseling and health, which can do certain forecasting work for discovering people’s mental health problems. The maximum prediction error of CNN and LSTM methods in predicting the characteristics of psychological counseling and health is only 2.64%.