Results
eNauka >
Results >
Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment
| Title: | Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment | Authors: | Wenzel, Julian; Dreschke, Nils; Hanssen, Esther; Rosen, Marlene; Ilanković, Andrej N.   ; Kambeitz, Joseph; Fett, Anne-Kathrin; Kambeitz-Ilankovic, Lana |
Issue Date: | 2024 | Publication: | European archives of psychiatry and clinical neuroscience | ISSN: | 0940-1334 European Archives of Psychiatry and Clinical Neuroscience Search Idenfier |
Publisher: | Berlin ; New York : Springer International | Type: | Article | Collation: | vol. 274 br. 7 str. 1639-1649 | DOI: | 10.1007/s00406-023-01668-w | WoS-ID: | 001069076500001 | Scopus-ID: | 2-s2.0-85171323128 | PMID: | 37715784 | PMCID: | PMC11422424 | URI: | https://enauka.gov.rs/handle/123456789/832487 | URL: | https://link.springer.com/article/10.1007/s00406-023-01668-w | Project: | NARSAD Young Investigator Award of Lana Kambeitz-Ilankovic through the Brain amp Behavior Research Foundation [28474] |
Metadata source: | (Preuzeto iz Nasi u WoS) | M-category: | 21M21 |
Items in eNauka are protected by copyright, with all rights reserved, unless otherwise indicated.