This paper is in the following e-collection/theme issue:

Depression and Mood Disorders; Suicide Prevention (1360) Artificial Intelligence (1360) Chatbots and Conversational Agents (530) Generative Language Models Including ChatGPT (304) Machine Learning (1458) Natural Language Processing (688) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1512) Methods and New Tools in Mental Health Research (453)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57362, first published .
The Most Effective Interventions for Classification Model Development to Predict Chat Outcomes Based on the Conversation Content in Online Suicide Prevention Chats: Machine Learning Approach

The Most Effective Interventions for Classification Model Development to Predict Chat Outcomes Based on the Conversation Content in Online Suicide Prevention Chats: Machine Learning Approach

The Most Effective Interventions for Classification Model Development to Predict Chat Outcomes Based on the Conversation Content in Online Suicide Prevention Chats: Machine Learning Approach

Authors of this article:

Salim Salmi1 Author Orcid Image ;   Saskia Mérelle1 Author Orcid Image ;   Renske Gilissen1 Author Orcid Image ;   Rob van der Mei2 Author Orcid Image ;   Sandjai Bhulai3 Author Orcid Image
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