Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Sander Siepel"'
Autor:
Sander Siepel, Tariq A. Dam, Lucas M. Fleuren, Diederik Gommers, Olaf L. Cremer, Rob J. Bosman, Sander Rigter, Evert-Jan Wils, Tim Frenzel, Dave A. Dongelmans, Remko de Jong, Marco Peters, Marlijn J.A Kamps, Dharmanand Ramnarain, Ralph Nowitzky, Fleur G.C.A. Nooteboom, Wouter de Ruijter, Louise C. Urlings-Strop, Ellen G.M. Smit, D. Jannet Mehagnoul-Schipper, Tom Dormans, Cornelis P.C. de Jager, Stefaan H.A. Hendriks, Sefanja Achterberg, Evelien Oostdijk, Auke C. Reidinga, Barbara Festen-Spanjer, Gert B. Brunnekreef, Alexander D. Cornet, Walter van den Tempel, Age D. Boelens, Peter Koetsier, Judith Lens, Harald J. Faber, A. Karakus, Robert Entjes, Paul de Jong, Thijs C.D. Rettig, Sesmu Arbous, Sebastiaan J.J. Vonk, Tomas Machado, Willem E. Herter, Armand R.J. Girbes, Mark Hoogendoorn, Patrick J. Thoral, Paul W.G. Elbers, Frank C. Bennis
Background: Identification of distinct clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment facilitating more personalized treatment. However,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56f4c17239013786d23b850db3446580
https://doi.org/10.21203/rs.3.rs-1328331/v1
https://doi.org/10.21203/rs.3.rs-1328331/v1
Autor:
Sander Siepel
Publikováno v:
On behalf of the Dutch ICU Data Sharing Collaborators 2023, ' Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment : An Unsupervised Machine Learning Analysis ', Journal of Intensive Care Medicine, vol. 38, no. 7, pp. 612-629 . https://doi.org/10.1177/08850666231153393
Journal of Intensive Care Medicine. SAGE Publications Inc.
Journal of Intensive Care Medicine. SAGE Publications Inc.
Background Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment. However, previous attempts did not take into account tempor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b172a2d9cd4960486238ed215314714
https://doi.org/10.1177/08850666231153393
https://doi.org/10.1177/08850666231153393
Publikováno v:
Köhler, M, Siepel, S & Treur, J 2021, ' The Interplay between Craving and Impulse Control : An Adaptive Network Model for Drug Addiction Treatment ', Procedia Computer Science, vol. 190, pp. 508-520 . https://doi.org/10.1016/j.procs.2021.06.059
BICA
Procedia Computer Science, 190, 508-520. Elsevier BV
BICA
Procedia Computer Science, 190, 508-520. Elsevier BV
This study introduces an adaptive causal network model of the effects of treatment on drug consumption in the case of addiction. Different factors are included that have been found to affect drug consumption and are impacted by addiction treatments.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::269a2a987629a3e7a9442e9557641e3b
https://hdl.handle.net/1871.1/887d3e19-fc68-4305-9a86-376879b90ec0
https://hdl.handle.net/1871.1/887d3e19-fc68-4305-9a86-376879b90ec0