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...

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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
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