Reply to paper ‘Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment’
Wenzel, J., Kambeitz, J., Fett, A-K. 
ORCID: 0000-0003-0282-273X & Kambeitz-Ilankovic, L. (2024).
Reply to paper ‘Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment’.
European Archives of Psychiatry and Clinical Neuroscience,
doi: 10.1007/s00406-024-01940-7
| Publication Type: | Article |
|---|---|
| Additional Information: | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00406-024-01940-7 |
| Subjects: | R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
| Departments: | School of Health & Psychological Sciences School of Health & Psychological Sciences > Psychology |
| SWORD Depositor: |
![[thumbnail of 20240926_Letter to the editor_final.pdf]](https://openaccess.city.ac.uk/style/images/fileicons/text.png)
Text
- Accepted Version
This document is not freely accessible until 30 November 2025 due to copyright restrictions.
Export
Downloads
Downloads per month over past year
Metadata
Metadata
MetadataAltmetric
CORE (COnnecting REpositories)
Actions (login required)
Actions (login required)
Admin Login