depression detection by using tweets
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Updated
Feb 10, 2019 - Python
depression detection by using tweets
A real time Multimodal Emotion Recognition web app for text, sound and video inputs
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
Edison AT is software Depression Assistant personal.
Deep Learning based research project for predicting mental state of a person.
Statistics for Suicide Analysis for all the countries in the world using Machine Learning Algorithms to find some interesting patterns, solutions and Clues about Suicides using Data Analysis and Data Visualizations
sMRI based depression classification using 3D volumetric convolutional networks
Prototype for predicting the severity of depression based on machine learning models deployed over the Google Cloud Platform using Firebase.
Pain; Neurosynth; MVPA; Mediation
Predicting depression from daily gross motor activity
Android application for Identification of stress symptoms, comparison and remedial solutions provided through chat-bot(Neo).
Can LMs generate useful synthetic data for the mental health domain?
Prompt: والحرب تجعل كل شيءٍ واضحٍ .... 🖊 Output: No depression e` Propability of 99.9% 🧠⏳
Codes for paper:A Prompt-Based Learning Approach for Few-Shot Social Media Depression Detection
Website for depression analysis by using LSTM-based model to classify depressive tweets.
This chatbot tries to imitate how depressed people think.
machine learning models for predicting depression based on EEG data
2D and 3D deformable CNN Autoencoders
Telegram bot used to test whether user have depression or no.
The Depression Dataset - Data Analysis
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