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

Machine Learning (2062) Advanced Data Analytics in eHealth (208) Decision Support for Health Professionals (1528) Clinical Information and Decision Making (1903) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2095) Methods and New Tools in Mental Health Research (555) Innovations in Mental Health Systems (480) Artificial Intelligence (2102)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/64617, first published .
An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study

An Interpretable Model With Probabilistic Integrated Scoring for Mental Health Treatment Prediction: Design Study

Authors of this article:

Anthony Kelly1, 2 Author Orcid Image ;   Esben Kjems Jensen3 Author Orcid Image ;   Eoin Martino Grua1 Author Orcid Image ;   Kim Mathiasen4, 5 Author Orcid Image ;   Pepijn Van de Ven1, 2 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Wang P, Liu H, Shi Y, Liu A, Zhu Q, Albu I, Pacholec M, Cheng L, Sun X, Chi X. Harnessing Small‐Data Machine Learning for Transformative Mental Health Forecasting: Towards Precision Psychiatry With Personalised Digital Phenotyping. Med Research 2025;1(2):226 View
  2. Kelly A, Bhardwaj N, Holmberg Sainte-Marie T, Van de Ven P, Melia R, Williams J, Mathiasen K, Nielsen A. Investigating how clinicians form trust in an AI-based mental health model: A qualitative case study (Preprint). JMIR Human Factors 2025 View