AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques

AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques

As suicide rates increase globally, there is a growing need for effective, data-driven methods in mental health monitoring. This study leverages advanced artificial intelligence (AI), particularly natural language processing (NLP) and machine learning (ML), to identify suicidal ideation from Twitter...

Full description

Saved in:
Bibliographic Details
Main Authors: Hesham Allam, Chris Davison, Faisal Kalota, Edward Lazaros, David Hua
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Big Data and Cognitive Computing
Subjects:
machine learning
artificial intelligence
suicidal ideation detection
mental health analysis
natural language processing
sentiment analysis
Online Access:https://www.mdpi.com/2504-2289/9/1/16
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items