hyoujinn/VOIDNET

Detección temprana de señales de depresión y riesgo suicida usando Inteligencia Artificial y Procesamiento del Lenguaje Natural (PLN)

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paranjaa/ece1508-student-depression-project

Class Project for ECE1508

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AnandaRauf/Edison-AT-Emotional-Depression-Assistant-

Edison AT is software Depression Assistant personal.

Language: Python - Size: 2.77 MB - Last synced at: 7 days ago - Pushed at: about 3 years ago - Stars: 14 - Forks: 3

Delos-343/Depresso-Espresso

Image-Based Depression Detection via RESNET Transfer over a Topological CNN Architecture

Language: Python - Size: 1.05 GB - Last synced at: 22 days ago - Pushed at: 22 days ago - Stars: 1 - Forks: 0

hariharitha21/Detection-of-Anxiety-and-Depression

Detecting Anxiety and Depression using facial emotion recognition and speech emotion recognition. Written in pythonPython

Language: Jupyter Notebook - Size: 16.5 MB - Last synced at: 19 days ago - Pushed at: almost 4 years ago - Stars: 58 - Forks: 5

ansh-d23/Well-Wise

Well Wise is a healthcare platform focused on mental health detection and management using machine learning and various advanced technologies. It is specifically designed to tackle the challenges of diagnosing and managing depression.

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stevenshci/FacePsy

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".

Language: C++ - Size: 81.5 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 29 - Forks: 3

DrTuryalai/ERBMA-Net

This repository contains the implementation of Enhanced Random Binary Multilevel Attention Network (ERBMA-Net), a novel framework for facial depression recognition. ERBMA-Net addresses key limitations in existing methods by introducing random binary convolutional filters for enhanced adaptability and multilevel attention mechanisms.

Language: Python - Size: 88.9 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

Amey-Thakur/DEPRESSION_DETECTION_USING_TWEETS

Twitter Depression Detection

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mike-coding/CS4980-GutMetagenome-ML-Project

Training classification models on human gut metagenomic signatures

Language: Python - Size: 4.89 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

divertingPan/OpticalDR

OpticalDR: A Deep Optical Imaging Model for Privacy-Protective Depression Recognition

Size: 1000 Bytes - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 6 - Forks: 0

divertingPan/STA-DRN

code for paper 'Spatial-Temporal Attention Network for Depression Recognition from Facial Videos'

Language: Python - Size: 25.4 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 26 - Forks: 2

kassy11/daicwoz_voice

Preprocessing and feature extraction for raw voice data of DAIC-WOZ

Language: Python - Size: 1.95 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

sahasourav17/Student-Anxiety-and-Depression-Prediction

A ML project specifically build for predicting students' mental health

Language: Jupyter Notebook - Size: 10.3 MB - Last synced at: 18 days ago - Pushed at: over 2 years ago - Stars: 23 - Forks: 1

javaidiqbal11/depression-detection-using-data-mining-association

This reo for the depression detection in tweets dataset using Data Mining Association rules and Machine Learning.

Language: Jupyter Notebook - Size: 720 KB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

jamespeilunli/clarity-ai

Depression and anxiety detection on social media with ML - first place in UTD's 2024 AI workshop

Language: CSS - Size: 101 MB - Last synced at: 4 months ago - Pushed at: 5 months ago - Stars: 9 - Forks: 1

TristanDos/ML-Classifiers-for-the-National-Income-Dynamics-Study-NIDS-

Research Repository for Honours Research Project at University of Witwatersrand 2024

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AKC23/Harnessing-LLMs-over-transformer-models-for-detecting-Bengali-depressive-text-A-comprehensive-study

Harnessing large language models over transformer models for detecting Bengali depressive social media text: A comprehensive study

Language: Jupyter Notebook - Size: 20.3 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 1

BashMocha/Automated-Depression-Detectiom-from-Tweets

The source code and dataset for comparing NLP techniques used to detect depression from tweets, including preprocessing, model implementations, and evaluation metrics.

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skaurl/depression-diary

Language: Java - Size: 451 KB - Last synced at: 8 months ago - Pushed at: almost 4 years ago - Stars: 5 - Forks: 1

gabby-01/Depression-Classification-Through-Natural-Language-Processing-Of-Social-Networking-Sites

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

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SUBHADIPMAITI-DEV/Depression-Detection-System-Using-Machine-Learning

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.

Language: Jupyter Notebook - Size: 4.95 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 10 - Forks: 2

Vibhuarvind/Detection-of-Depression-Using-Late-Fusion-of-Sequential-Actigraphy-Features 📦

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.

Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: 9 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

brunomontezano/app-depressao

Web app para auto-aplicação da escala PHQ-9 para depressão.

Language: R - Size: 28.5 MB - Last synced at: about 2 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

shubhamjainjnsb/Anti_depression_ROBOT

Here we aim to develop a software plus hardware that uses AI based algorithms to determine if the user is under any sort of physical/mental/emotional trauma and thus under any sort of depression. The bot is capable of generating an report for the user and also alerts his/her care-taker in case of threats to life and severe symptoms of depression using the GSM module. Also using the camera module the Chatbot is capable of deterring the mood of the user using facial expressions. The chatbot is very interactive with the user and can perform tasks such as setting alarms, remainders, to-do-lists etc. The chatbot is integrated into Raspberry Pi3 and thus converted into a mobile robot which follows its user and then interacts . The robot is fitted with sensors to detect fire, smoke and gas in case of emergencies. And Our research shows that by using this chat-bot the level of depression of user decreases gradually.

Language: Python - Size: 166 KB - Last synced at: 11 months ago - Pushed at: almost 3 years ago - Stars: 3 - Forks: 1

sta314/federated-depression-detection

Depression detection with federated learning

Language: Jupyter Notebook - Size: 2.67 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

cosmaadrian/multimodal-depression-from-video

Official source code for the paper: "Reading Between the Frames Multi-Modal Non-Verbal Depression Detection in Videos"

Language: Python - Size: 370 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 20 - Forks: 2

sayantikabanik/Depression_marker_detection

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

Language: Jupyter Notebook - Size: 5.41 MB - Last synced at: 3 months ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

Mo-Shaeerah/Predict-Depression-by-Words-

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

Language: Jupyter Notebook - Size: 21.7 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

NafisHandoko/depr-calc

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

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Nihalahamad1905/DEPRESSION-DETECTION-USING-MACHINE-LEARNING

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.

Language: HTML - Size: 27.4 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

cosmaadrian/time-enriched-multimodal-depression-detection

Official source code for the paper: "It’s Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers"

Language: Python - Size: 579 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 32 - Forks: 1

ArfaNada/PFE-Project

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

Language: Python - Size: 13.7 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

chanapapan/Depression-Detection

Comparing Selective Masking Methods for Depression Detection in Social Media

Language: Python - Size: 7.69 MB - Last synced at: 11 months ago - Pushed at: almost 2 years ago - Stars: 9 - Forks: 1

hamza2306/Mentoso

Mentoso : Mental health detection and Counselling application

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akebu6/ML-Depression-Detection

This is a repo for a side project about detecting depression using ML

Size: 10.7 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

AnandaRauf/Depression-Asisstant-GDSC-Challenge-Solution-

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

Language: Python - Size: 5.17 MB - Last synced at: 21 days ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 1

iremhttp/DepressionDetection

Text-Based Depression Detection By Machine Learning

Language: Jupyter Notebook - Size: 10.2 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Vibhuarvind/Depression-Detect

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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AnandaRauf/Multimodal-Emotion-Recognition Fork of maelfabien/Multimodal-Emotion-Recognition

A real time Multimodal Emotion Recognition web app for text, sound and video inputs

Size: 1.03 GB - Last synced at: 11 months ago - Pushed at: almost 4 years ago - Stars: 9 - Forks: 4

aksharbhayani/ProjectX

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

Language: Dart - Size: 12.3 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

nitrotap/mental-health-check

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

Language: JavaScript - Size: 171 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 22 - Forks: 15

kishanmaharaj/Actigraphy-based-Depression-Analysis

Predicting depression from daily gross motor activity

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NM001007/An-Attention-based-Hybrid-Suicide-Ideation-Detection

This is an implementation of the attention-based hybrid architecture (Ghosh et al, 2023) for suicide/depressive social media notes detection.

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Sans003/PeopleJsonViewer

no description, just suffering

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AleystreV/TEDDY

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

Language: Python - Size: 4.5 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

aaronstone1699/Depression-detection

Depression is one of the most common mental disorders with millions of people suffering from it.It has been found to have an impact on the texts written by the affected masses.In this study our main aim was to utilise tweets to predict the possibility of a user at-risk of depression through the use of Natural Language Processing(NLP) tools and deep learning algorithms.LSTM has been used as a baseline model that resulted in an accuracy of 95.12% and an F1 score of 0.9436. We implemented a hybrid Bi-LSTM + CNN model which we trained on learned embeddings from the tweet dataset was able to improve upon previous works and produce precision and recall of 0.9943 and 0.9988 respectively,giving an F1 score of 0.9971.

Language: Python - Size: 6.9 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 13 - Forks: 3

sofieditmer/depression_detection

This repository contains the contents of a Master's degree in Cognitive Science thesis project concerned with assessing the generalizability of machine learning models for depression detection in transcribed clinical interviews with patients diagnosed with chronic and first-episode major depressive disorder (MDD).

Language: Jupyter Notebook - Size: 4.14 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

sidmulajkar/sentiment-predictor-for-stress-detection

Voice stress analysis (VSA) aims to differentiate between stressed and non-stressed outputs in response to stimuli (e.g., questions posed), with high stress seen as an indication of deception. In this work, we propose a deep learning-based psychological stress detection model using speech signals. With increasing demands for communication between humans and intelligent systems, automatic stress detection is becoming an interesting research topic. Stress can be reliably detected by measuring the level of specific hormones (e.g., cortisol), but this is not a convenient method for the detection of stress in human- machine interactions. The proposed algorithm first extracts Mel- filter bank coefficients using pre-processed speech data and then predicts the status of stress output using a binary decision criterion (i.e., stressed or unstressed) using CNN (Convolutional Neural Network) and dense fully connected layer networks.

Language: Jupyter Notebook - Size: 224 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 40 - Forks: 13

cristinaa23/Depression_TopicModeling

Language model capable of detecting emerging topics from Reddit posts with depression as main theme using the Latent Dirichlet Allocation (LDA) method.

Language: Jupyter Notebook - Size: 34.6 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

VGandhi27/Depression-Detection-using-Naive-Bayes

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

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Aafreen2603/Sentiment-analysis-depression-detection

Language: Jupyter Notebook - Size: 955 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

rafalposwiata/depression-detection-lt-edi-2022

This repository contains the code of our winning solution for the Shared Task on Detecting Signs of Depression from Social Media Text at LT-EDI-ACL2022.

Language: Python - Size: 8.11 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 4 - Forks: 3

AmirHoseein99/Depression-Engine

Detecting depressed Patient based on Speech Activity, Pauses in Speech and Using Deep learning Approach

Language: Python - Size: 1.2 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 12 - Forks: 2

BouzidiImen/Social_media_Prediction_depression

This consists in using a variety of social networks data, including both images and texts, to detect early signs of depression.

Language: Jupyter Notebook - Size: 9.2 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 7 - Forks: 5

wywyWang/Depression-Detection-LT-EDI-ACL-2022

Official Implementation for NYCU_TWD LT-EDI@ACL 2022

Language: Python - Size: 110 KB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 13 - Forks: 3

thalia-huynh/predicting-depression-using-nlp

Predicting depression using Twitter posts

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Akshat2430/Detecting-Depression-From-Speech-Signals

Speech-based diagnosis of depression

Language: Python - Size: 27.3 KB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 12 - Forks: 4

notmanan/Depression-Detection-Through-Multi-Modal-Data

Conventionally depression detection was done through extensive clinical interviews, wherein the subject’s re- sponses are studied by the psychologist to determine his/her mental state. In our model, we try to imbibe this approach by fusing the 3 modalities i.e. word context, audio, and video and predict an output regarding the mental health of the patient. The output is divided into a binary yes/no denoting whether the patient has symptoms of depression. We’ve built a deep learning model that fuses these 3 modalities, assigning them appropriate weights, and thus gives an output.

Language: Jupyter Notebook - Size: 582 KB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 42 - Forks: 24

eddieir/Depression_detection_using_Twitter_post

depression detection by using tweets

Language: Python - Size: 494 KB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 9 - Forks: 7

faiqali1/Suicidal-Text-Analysis

Using Machine Learning to predict if text is suicidal.

Language: Jupyter Notebook - Size: 4.87 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 6 - Forks: 1

theatina/Stress_Detection

M.Sc. mini project for NLP class (M908)

Language: Python - Size: 79.5 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

saket0510/Identifying-people-with-depression-based-on-social-media-presence-using-bidirectional-LSTM

A Bidirectional LSTM model is built to detect depressive tweets. This model is also compared with other models like GRU and LSTM

Language: Jupyter Notebook - Size: 388 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 1

restradap001/Depression-in-Mexico

Instrumento para la detección de la depresión en jóvenes mexicanos

Language: Jupyter Notebook - Size: 19.7 MB - Last synced at: about 2 years ago - Pushed at: almost 4 years ago - Stars: 2 - Forks: 0

helemanc/COVID19-twitter-depression

Analysis of labeling strategies aimed at identifying depression phenomena among users’ tweets.

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NANDINI-star/Predicting-Depression-from-Social-Netwroking-Data-using-Machine-Learning-Techniques

Language: Jupyter Notebook - Size: 556 KB - Last synced at: almost 2 years ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 1

genaromateu/FinalProyectPLN

se diseñó un modelo para detectar depresión en usuarios en base a comentarios en redes sociales

Language: Jupyter Notebook - Size: 14.6 MB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 2