Identifying depression markers via social media and building an early-stage recommendation engine

Depression Calculator as a Final Project for Datamining Subject in the College

A trained machine learning model to detect early symptoms of depression using data collected from X (Twitter) that is integrated into Telegram.

Prompt: والحرب تجعل كل شيءٍ واضحٍ .... 🖊 Output: No depression e` Propability of 99.9% 🧠⏳

Depression Asisstant can help you give solution. Please using Python version 3.9.5 for contribute.

Extract explainablity from RoBERTa 🪆 ad Born 🐈 while classifying depresson 🎭

DAEB-τSS3: Imbalanced Social Media Text Depression Detection Method

A mobile application to detect the depression level in patients by facial and Twitter analysis.

Twitter Depression Detection

This is an academic final year individual project, published by Liew Jun Yen - Data Analyst

Analyzed time-series data (Depressjon) to detect depression from patient activity recorded via clinical actigraphy watches. Utilized features such as time domain, statistical metrics, and LSTM-extracted attributes.

Predicting depression using Twitter posts

Undergraduate Project - Application of Monitoring and Recording Depression Emotions

This Project creates a smart AI computer program that predicts depression from what people write online. It learns patterns in language to spot signs of depression, helping identify those who might need support.

Text-Based Depression Detection By Machine Learning

Internal Healthn uses AI technology and social media as a tool for mental health care

According to the World Health Organization, depression is the leading cause of disability worldwide. Globally, more than 300 million people of all ages suffer from the disorder. And the incidence of the disorder is increasing everywhere. Depression is a complex condition, involving many systems of the body

T.E.D.D.Y aims to help teachers and counselors analyze student essays to find potential depressive/suicidal sentiment and offer support.