Predicting depression from acoustic features of speech using a Convolutional Neural Network.

A curated list of awesome mental health resources

The first asian machine learning in Jeju Island, South Korea - Project

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😔 😞 😣 😖 😩 Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"

Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction (ICANN 2021)

Internet Delivered Treatment using Adaptive Technology

MoodSnap mood diary. A free mood diary app with analytics for iOS, made for everybody, written with features for people with mood disorders in mind.

Healing self-talk through Node-based CLI

A mental health quiz app to help individuals check in with themselves.

Depression Detection from Speech

Official implementation of the affective mobile sensing system called FacePsy proposed in the article "FacePsy: An Open-Source Affective Mobile Sensing System - Analyzing Facial Behavior and Head Gesture for Depression Detection in Naturalistic Settings".

Detect Depression from Social Network Using Deep learning

A Scraper that scrapes '#depression' tweets daily powered by GitHub action and snscrape (stopped at June 30,2023)

A visual representation of depressive thoughts.

This project develops a Depression Detection System using Machine Learning on Twitter data. It predicts depression by analyzing tweets with SVM, Logistic Regression, Decision Trees, and NLTK in Python.

Octahacks 3.0 - Team Coderaptors

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Depression web app with text emotion/depression classification and personality/depression test using 4 deep learning models. Demonstrate end-to-end pipeline from training in Python to edge deployment in Typescript