Record link: 
https://doi.org/10.34726/hss.2026.139551
http://hdl.handle.net/20.500.12708/230995
-
Title: 
Clinically interpretable prediction of chronic pain from non-invasive multimodal data
en
Citation: 
Stier, A. B. (2026). Clinically interpretable prediction of chronic pain from non-invasive multimodal data [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.139551
-
reposiTUm DOI: 
10.34726/hss.2026.139551
-
CatalogPlus: 
AC18028491
-
Publication Type: 
Thesis - Diplomarbeit
en
Language: 
English
-
Authors: 
Stier, Alma Beatrix 
-
Advisor: 
Rattay, Frank 
-
Organisational Unit: 
E101 - Institut für Analysis und Scientific Computing 
-
Date (published): 
2026
-
Number of Pages: 
79
-
Keywords: 
chronische Schmerzen; Abschätzung; Modellierung
de
 
chronic pain; pain assessment; modeling pain
en
Additional information: 
Arbeit an der Bibliothek noch nicht eingelangt - Daten nicht geprueft - gesperrte Arbeit (bis 2028-09-01+02:00)
-
License: 
In Copyright
de
Appears in Collections:
Thesis

Fulltext (Version of Record (published version))
Adobe PDF
(6.62 MB)
Open Access In Copyright
Embargo. Accessible from 01.10.2028
Show full item record

Page view(s)

5
checked on Sep 22, 2026

Download(s)

1
checked on Sep 22, 2026

Google ScholarTM

Check