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

A visual representation of depressive thoughts.

Using Artificial Intelligence to distinguish between suicidal and depressive messages (4th Place Congressional App Challenge)

Visualizing suicide data with javascript libraries

A social chatbot for people in depression and suicidal condition.

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

Lend a Hand is a Chrome extension to detect whether user is searching for or posting suicidal ideation on social media and interrupts their train of thought to provide helpful resources. Part of the #ColorALife project.

Suicide chess engine acting as desktop engine, web page, mobile application, Internet chess server and library

This repo contains my final work for my class in Natural Language Processing, part of the MSc in Data Science and Business Analytics @ Bocconi University

A list of suicide helplines, organized by country.

Data Analysis of suicides in India

The baseline code for the CLPsych 2021 Shared Task.

A basic machine learning project for studying and analysing WHO suicide statistics collected since 1979. We used python as the programming language, Spider as the IDE for coding, and such well-known libraries as Numpy (for using mathematical functions and working with arrays), Pandas (for analyzing data from files), matplotlib (for visualizing d…

Repository for Data Mining Approach to the Detection of Suicide in Social Media: A Case Study of Singapore

This thesis work introduces a new machine learning method to estimate the risk of suicide in bangladeshi students enrolled in colleges, universities, and madrasahs.

This project explores underlying factors contributing to farmer suicides in India and facilitating targeted interventions. Using advanced data visualization techniques, this report provides a comprehensive analysis of several factors such as Regional trends and hotspots, causes & correlations etc.

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