Depression Detection is a speech-based classifier that analyzes emotional and acoustic features to detect depression.
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Updated
Sep 24, 2024 - Jupyter Notebook
Depression Detection is a speech-based classifier that analyzes emotional and acoustic features to detect depression.
Codes for paper:A Prompt-Based Learning Approach for Few-Shot Social Media Depression Detection
Can LMs generate useful synthetic data for the mental health domain?
The Depression Dataset - Data Analysis
Prompt: والحرب تجعل كل شيءٍ واضحٍ .... 🖊 Output: No depression e` Propability of 99.9% 🧠⏳
Website for depression analysis by using LSTM-based model to classify depressive tweets.
Depression and Suicidal Thoughts Support Chat App
Predicting depression from daily gross motor activity
Prototype for predicting the severity of depression based on machine learning models deployed over the Google Cloud Platform using Firebase.
2D and 3D deformable CNN Autoencoders
machine learning models for predicting depression based on EEG data
Telegram bot used to test whether user have depression or no.
Edison AT is software Depression Assistant personal.
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
Android application for Identification of stress symptoms, comparison and remedial solutions provided through chat-bot(Neo).
A real time Multimodal Emotion Recognition web app for text, sound and video inputs
Deep Learning based research project for predicting mental state of a person.
This chatbot tries to imitate how depressed people think.
Pain; Neurosynth; MVPA; Mediation
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
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