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

Innovations in Mental Health Systems (418) Methods and New Tools in Mental Health Research (497) Natural Language Processing (796) Machine Learning (1723) Artificial Intelligence (1710) Clinical Information and Decision Making (1639)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49894, first published .
Predicting Patients' Satisfaction With Mental Health Drug Treatment Using Their Reviews: Unified Interchangeable Model Fusion Approach

Predicting Patients' Satisfaction With Mental Health Drug Treatment Using Their Reviews: Unified Interchangeable Model Fusion Approach

Predicting Patients' Satisfaction With Mental Health Drug Treatment Using Their Reviews: Unified Interchangeable Model Fusion Approach

Authors of this article:

Yi Wang1 Author Orcid Image ;   Yide Yu1 Author Orcid Image ;   Yue Liu1 Author Orcid Image ;   Yan Ma1, 2 Author Orcid Image ;   Patrick Cheong-Iao Pang1 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

Journals

  1. Balch J, Chatham A, Hong P, Manganiello L, Baskaran N, Bihorac A, Shickel B, Moseley R, Loftus T. Predicting patient reported outcome measures: a scoping review for the artificial intelligence-guided patient preference predictor. Frontiers in Artificial Intelligence 2024;7 View
  2. Jin Y, Liu J, Li P, Wang B, Yan Y, Zhang H, Ni C, Wang J, Li Y, Bu Y, Wang Y. The Applications of Large Language Models in Mental Health: Scoping Review. Journal of Medical Internet Research 2025;27:e69284 View