Review on Deep Learning for Detection Psychological Disorder

Abstract

Early detection is a way to control the maximum loss. There are many cases that are handled by the early detection and decrease the further complex mental issues . Many research works have been done on the detection of psychological disorder. The Most common technique that is used in research is machine learning. There are many previous researches that conducted through the machine learning. Machine learning algorithms like decision tree, KNN, SVM, na¨ıve bays etc. gives the better performance in their own field. But now days, a new developed technique is used to predict the illness. The new developed technique is deep learning. Deep learning is used to overcome the drawbacks of machine learning. A deep learning technique that is mostly used in data science is Convolution neural network, Recurrent neural network, deep network etc. Deep learning algorithms gives the better results as compared to machine learning. In our research, CNN is used to classify the images. Basically our research is based on the CNN which is most popular technique for the data which is collected from medical surveys, patient’s interview, clinical data and social media post, signs. Analysing this all will make better prediction about the illness of psychological health, based on that accuracy of the diagnosis will be paramount.