Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Julie Josse"'
Autor:
Tobias Gauss, Jean-Denis Moyer, Clelia Colas, Manuel Pichon, Nathalie Delhaye, Marie Werner, Veronique Ramonda, Theophile Sempe, Sofiane Medjkoune, Julie Josse, Arthur James, Anatole Harrois, the Traumabase Group
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Importance Decision-making in trauma patients remains challenging and often results in deviation from guidelines. Machine-Learning (ML) enhanced decision-support could improve hemorrhage resuscitation. Aim To develop a ML enhanced decision s
Externí odkaz:
https://doaj.org/article/6c0cc9baa3124d98950b4a3b9984b28f
Autor:
Alice Blet, Joel B. McNeil, Julie Josse, Bernard Cholley, Raphaël Cinotti, Gad Cotter, Agnès Dauvergne, Beth Davison, Kévin Duarte, Jacques Duranteau, Marie-Céline Fournier, Etienne Gayat, Samir Jaber, Sigismond Lasocki, Thomas Merkling, Katell Peoc’h, Imke Mayer, Malha Sadoune, Pierre-François Laterre, Romain Sonneville, Lorraine Ware, Alexandre Mebazaa, Antoine Kimmoun
Publikováno v:
Critical Care, Vol 26, Iss 1, Pp 1-10 (2022)
Abstract Background Impact of in-ICU transfusion on long-term outcomes remains unknown. The purpose of this study was to assess in critical-care survivors the association between in-ICU red blood cells transfusion and 1-year mortality. Methods FROG-I
Externí odkaz:
https://doaj.org/article/6867e37feaf64c0a8d3d8e7c905a23c4
Publikováno v:
Journal of Statistical Software, Vol 73, Iss 1, Pp 1-18 (2016)
The Dutch and the French schools of data analysis differ in their approaches to the question: How does one understand and summarize the information contained in a data set? The commonalities and discrepancies between the schools are explored here wit
Externí odkaz:
https://doaj.org/article/d1017510b2e648648ffa1d7110ff95f5
Autor:
Julie Josse, François Husson
Publikováno v:
Journal of Statistical Software, Vol 70, Iss 1, Pp 1-31 (2016)
We present the R package missMDA which performs principal component methods on incomplete data sets, aiming to obtain scores, loadings and graphical representations despite missing values. Package methods include principal component analysis for cont
Externí odkaz:
https://doaj.org/article/eacaab5b2f4e44ba9998751ebfba603b
Publikováno v:
Journal of Statistical Software, Vol 25, Iss 1 (2008)
In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The main features of this package is the possibility to take into account different types of variables (quantitative or categorical), different types of stru
Externí odkaz:
https://doaj.org/article/5af5316926b244a8b337ca77448d80ac
Autor:
Amin Gharbi‐Meliani, Julie Josse, François Husson, Henri Vandendriessche, Eleonore Bayen, Kristine Yaffe, Anne‐Catherine Bachoud‐Levi, Laurent Cleret de Langavant
Publikováno v:
Alzheimer's & Dementia. 18
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8fc913f37e435b9108ec7ca9a4cd157d
https://doi.org/10.1002/alz.061796
https://doi.org/10.1002/alz.061796
Autor:
Wei Jiang, Veronika Rockova, Julie Josse, Szymon Majewski, Błażej Miasojedow, Małgorzata Bogdan
Publikováno v:
Journal of Computational and Graphical Statistics. 31:113-137
We consider the problem of variable selection in high-dimensional settings with missing observations among the covariates. To address this relatively understudied problem, we propose a new synergis...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::213592091dd25e51990d05a99b773107
https://doi.org/10.1080/10618600.2021.1963263
https://doi.org/10.1080/10618600.2021.1963263
BACKGROUND As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values: incomplete observations. These large databases are well suited to train machine-learning models, for instance for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c9bc173055f24e267747af4b468177a0
https://doi.org/10.17504/protocols.io.b3nfqmbn
https://doi.org/10.17504/protocols.io.b3nfqmbn
Publikováno v:
GigaScience
GigaScience, Oxford Univ Press, In press
HAL
GigaScience, In press, ⟨10.1093/gigascience/giac013⟩
GigaScience, Oxford Univ Press, In press
HAL
GigaScience, In press, ⟨10.1093/gigascience/giac013⟩
BACKGROUND: As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values: incomplete observations. These large databases are well suited to train machine-learning models, for instance for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d58af0cd27abe699ca9a990978172393
https://hal.archives-ouvertes.fr/hal-03526292
https://hal.archives-ouvertes.fr/hal-03526292
Autor:
Anatole Harrois, Jean-Pierre Nadal, Aliénor Dreyfus, Imke Meyer, Boutonnet Mathieu, Jean-Denis Moyer, Arthur G. James, Tobias Gauss, Arnaud Foucrier, Pierre-Julien Cungi, Julie Josse
Background: The CRASH-3 trial provides a high level of evidence on the question whether to administer Tranexamic Acid (TXA) for Traumatic brain injury (TBI). For numerous other research questions, the available evidence will not correspond to such a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b89f79b2947c02fb3f76fe3662efa955
https://hal.sorbonne-universite.fr/hal-03285078
https://hal.sorbonne-universite.fr/hal-03285078