Abstract:
Depression is a primary cause of mental illness and predicts early death. It also increases suicidal thoughts and impairs daily functioning. One in 15 adults suffers from depression annually, affecting 300 million people. Several empirical research have linked particular linguistic traits to depression and self-destructive conduct.
This Depression Detection System recommends psychiatrists for anxiety, PTSD, and bipolar depression at nearby clinics. Additionally, the user must describe himself for one minute while their facial expressions are captured. Answering all quiz questions is required.
That system uses Naive Bayes for the quiz. CNN and an exclusive Depression face dataset will be generated for Image & Video. This algorithm advises nearby clinics to see a psychiatrist based on depression kind.
This system uses Python. The front end uses HTML, CSS, and JavaScript, and the back end uses MySQL. Here, we used Django.
Humans’ greater emotions and feelings can be blended with technology to develop beneficial tools. Depression self-evaluation and diagnosis accuracy are greatly improved by this depression detection technique. The user must also describe themselves for one minute to determine facial expression.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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