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.
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Updated
Sep 24, 2024 - Jupyter Notebook
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.
The source code and dataset for comparing NLP techniques used to detect depression from tweets, including preprocessing, model implementations, and evaluation metrics.
Depression detection on social media with ML - first place in UTD's 2024 AI workshop
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.
Web app para auto-aplicação da escala PHQ-9 para depressão.
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.
This is an academic final year individual project, published by Liew Jun Yen - Data Analyst
Harnessing large language models over transformer models for detecting Bengali depressive social media text: A comprehensive study
Depression detection with federated learning
Official source code for the paper: "Reading Between the Frames Multi-Modal Non-Verbal Depression Detection in Videos"
Prompt: والحرب تجعل كل شيءٍ واضحٍ .... 🖊 Output: No depression e` Propability of 99.9% 🧠⏳
Depression detection using machine learning is a vital area of research given the global burden of mental health disorders. This project explores two primary methodologies: leveraging depression quiz tests and analyzing sentences.
A trained machine learning model to detect early symptoms of depression using data collected from X (Twitter) that is integrated into Telegram.
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.
Twitter Depression Detection
OpticalDR: A Deep Optical Imaging Model for Privacy-Protective Depression Recognition
code for paper 'Spatial-Temporal Attention Network for Depression Recognition from Facial Videos'
Mentoso : Mental health detection and Counselling application
This is a repo for a side project about detecting depression using ML
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