Sentimental Analysis Using Deep Learning For Psychological Diagnosis

Sentiment analysis is the process of managing feelings, opinions. The demand to analyze and organize unstructured data obtained from social media in the form of hidden information has increased the need for sentiment analysis. The research covered in this paper focuses on people with mental illnesses. After speaking with a large number of patients, it became clear why some of them were reluctant to meet with doctors . Even patients' family did not feel very comfortable visiting doctors. Constraints are the main factors in the Asian context. If the public learns that a patient is seeing a mental health professional, they label him as insane. This forces patients and their family members to conceal their disease and avoid seeing the doctors.The second and most significant factor is that patients refuse to acknowledge that they are dealing with a mental illness.In this study,researchers will put up a creative idea for assisting and enhancing the care of someone with psychological distress. The suggested remedy will build a learning pattern from the assessed input data and compare it to the tested model. Based on the prior treatment of the patient's repository in text form, it offer insightful information that helps psychologists diagnose their patients effectively. Both the patient and the psychiatrist will benefit from the suggested remedy. Inputs: Doctor's evaluation form in digital format. Deep learning: Training model developed from repository of prior treatment records.