The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment.
- DOI
- 10.3389/fpsyt.2026.1683069
- Published
- 2026
- Container
- Frontiers in psychiatry
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3389/fpsyt.2026.1683069,
title = {The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment.},
author = {Raabe FJ and Brechtel S and Lugmair C and Weiser J and Schiltz K and Koutsouleris N and Falkai P and Hoch E and Pogarell O and Koller G and Popovic D},
year = {2026},
journal = {Frontiers in psychiatry},
doi = {10.3389/fpsyt.2026.1683069},
url = {https://doi.org/10.3389/fpsyt.2026.1683069}
}RIS
TY - JOUR TI - The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment. AU - Raabe FJ AU - Brechtel S AU - Lugmair C AU - Weiser J AU - Schiltz K AU - Koutsouleris N AU - Falkai P AU - Hoch E AU - Pogarell O AU - Koller G AU - Popovic D PY - 2026 JO - Frontiers in psychiatry DO - 10.3389/fpsyt.2026.1683069 UR - https://doi.org/10.3389/fpsyt.2026.1683069 ER -
APA
FJ, R., S, B., C, L., J, W., K, S., N, K., P, F., E, H., O, P., G, K., & D, P. (2026). The patterns of relapse and abstinence: using machine learning to identify a multidimensional signature of long-term outcome after inpatient alcohol withdrawal treatment.. Frontiers in psychiatry. https://doi.org/10.3389/fpsyt.2026.1683069
Source records
- pubmed · retrieved 2026-09-26T18:18:02.777Z