Rezultati

eNauka >  Rezultati >  Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment
Naziv: Ecological momentary assessment (EMA) combined with unsupervised machine learning shows sensitivity to identify individuals in potential need for psychiatric assessment
Autori: Wenzel, Julian; Dreschke, Nils; Hanssen, Esther; Rosen, Marlene; Ilanković, Andrej N.  ; Kambeitz, Joseph; Fett, Anne-Kathrin; Kambeitz-Ilankovic, Lana
Godina: 2024
Publikacija: European archives of psychiatry and clinical neuroscience
ISSN: 0940-1334 European Archives of Psychiatry and Clinical Neuroscience Pretraži identifikator
Izdavač: Berlin ; New York : Springer International
Tip rezultata: Naučni članak
Kolacija: 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
Projekat: NARSAD Young Investigator Award of Lana Kambeitz-Ilankovic through the Brain amp
Behavior Research Foundation
[28474]
Izvor metapodataka: (Preuzeto iz Nasi u WoS)
M-kategorija: 
21M21 - Vodeći međunarodni časopis kategorije M21

8
SCOPUSTM
3
PubMed CentralTM
6
WEB OF SCIENCETM
Alt metrika
Dimensions
Unpaywall

Rezultati na eNauka su zaštićeni autorskim pravima i sva prava su zadržana, osim ako nije drugačije naznačeno.