Inproceedings,
Multi-stakeholder Approach for Designing an AI Model to Predict Treatment Adherence.
B. Merino-Barbancho, P. Arroyo, M. Rujas, A. Cipric, N. Ciccone, F. Lupiáñez-Villanueva, A. Würth, F. Folkvord, M. Cabrera, M. Arredondo, and G. Fico.HCI (19), volume 14029 of Lecture Notes in Computer Science, page 260-271. Springer, (2023)
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- conf/hci/MerinoBarbanchoARCCLWFCAF23
- entry type
- inproceedings
- booktitle
- HCI (19)
- year
- 2023
- pages
- 260-271
- publisher
- Springer
- series
- Lecture Notes in Computer Science
- volume
- 14029
- crossref
- conf/hci/2023-19
- ee
- https://doi.org/10.1007/978-3-031-35748-0_19
- isbn
- 978-3-031-35748-0
- url
- http://dblp.uni-trier.de/db/conf/hci/hci2023-19.html#MerinoBarbanchoARCCLWFCAF23
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- please select -%0 Conference Paper
%1 conf/hci/MerinoBarbanchoARCCLWFCAF23
%A Merino-Barbancho, Beatriz
%A Arroyo, Peña
%A Rujas, Miguel
%A Cipric, Ana
%A Ciccone, Nicholas
%A Lupiáñez-Villanueva, Francisco
%A Würth, Ana Roca-Umbert
%A Folkvord, Frans
%A Cabrera, María Fernanda
%A Arredondo, María Teresa
%A Fico, Giuseppe
%B HCI (19)
%D 2023
%E Duffy, Vincent G.
%I Springer
%K dblp
%P 260-271
%T Multi-stakeholder Approach for Designing an AI Model to Predict Treatment Adherence.
%U http://dblp.uni-trier.de/db/conf/hci/hci2023-19.html#MerinoBarbanchoARCCLWFCAF23
%V 14029
%@ 978-3-031-35748-0
@inproceedings{conf/hci/MerinoBarbanchoARCCLWFCAF23,
added-at = {2023-11-12T00:00:00.000+0100},
author = {Merino-Barbancho, Beatriz and Arroyo, Peña and Rujas, Miguel and Cipric, Ana and Ciccone, Nicholas and Lupiáñez-Villanueva, Francisco and Würth, Ana Roca-Umbert and Folkvord, Frans and Cabrera, María Fernanda and Arredondo, María Teresa and Fico, Giuseppe},
biburl = {https://www.bibsonomy.org/bibtex/2fe21e63b6a7361ad736ec9c30253f0cd/dblp},
booktitle = {HCI (19)},
crossref = {conf/hci/2023-19},
editor = {Duffy, Vincent G.},
ee = {https://doi.org/10.1007/978-3-031-35748-0_19},
interhash = {12541116c120b5cb5aaf97a545dcc298},
intrahash = {fe21e63b6a7361ad736ec9c30253f0cd},
isbn = {978-3-031-35748-0},
keywords = {dblp},
pages = {260-271},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
timestamp = {2024-04-09T11:39:05.000+0200},
title = {Multi-stakeholder Approach for Designing an AI Model to Predict Treatment Adherence.},
url = {http://dblp.uni-trier.de/db/conf/hci/hci2023-19.html#MerinoBarbanchoARCCLWFCAF23},
volume = 14029,
year = 2023
}