depression detection by using tweets
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Updated
Feb 10, 2019 - Python
depression detection by using tweets
Depression is one of the most common mental disorders with millions of people suffering from it.It has been found to have an impact on the texts written by the affected masses.In this study our main aim was to utilise tweets to predict the possibility of a user at-risk of depression through the use of Natural Language Processing(NLP) tools and …
A real time Multimodal Emotion Recognition web app for text, sound and video inputs
A mobile application to detect the depression level in patients by facial and Twitter analysis.
Speech-based diagnosis of depression
Detecting Anxiety and Depression using facial emotion recognition and speech emotion recognition. Written in pythonPython
Instrumento para la detección de la depresión en jóvenes mexicanos
se diseñó un modelo para detectar depresión en usuarios en base a comentarios en redes sociales
My final year dissertation project. This project takes motor activity data from a control group and a condition group. The data is filtered, cleaned and transformed for appropriate use to find the "best" classification algorithm to identify depressed patients from non-depressed patients
Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed), with high stress seen as an indication of deception. In this work, we propose a deep learning-based psychological stress detection model using speech signals. With increasing demands for communication betwee…
Depression Calculator as a Final Project for Datamining Subject in the College
A Bidirectional LSTM model is built to detect depressive tweets. This model is also compared with other models like GRU and LSTM
Edison AT is software Depression Assistant personal.
Depression Asisstant can help you give solution. Please using Python version 3.9.5 for contribute.
Analysis of labeling strategies aimed at identifying depression phenomena among users’ tweets.
Identifying depression markers via social media and building an early-stage recommendation engine
Depression Detect is a web app which enables clinicians to use sensing technologies with a focus on acoustic characteristics and facial landmarks to detect depression.
Undergraduate Project - Application of Monitoring and Recording Depression Emotions
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