Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Cedric, Bousquet"'
Autor:
Alexandre Dupuy-Zini, Bissan Audeh, Christel Gérardin, Catherine Duclos, Amandine Gagneux-Brunon, Cedric Bousquet
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e37237 (2023)
BackgroundWithin a few months, the COVID-19 pandemic had spread to many countries and had been a real challenge for health systems all around the world. This unprecedented crisis has led to a surge of online discussions about potential cures for the
Externí odkaz:
https://doaj.org/article/d38790fe281e42ac9c0d7e0bdaacc41d
Publikováno v:
IEEE Transactions on Automation Science and Engineering. :1-16
Publikováno v:
Studies in health technology and informatics. 295
In previous work, we implemented a deep learning model with CamemBERT and PyTorch, and built a microservices architecture using the TorchServe serving library. Without TorchServe, inference time was three times faster when the model was loaded once i
In previous work, we implemented a deep learning model with CamemBERT and PyTorch, and built a microservices architecture using the TorchServe serving library. Without TorchServe, inference time was three times faster when the model was loaded once i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b68e1b13f924b46a5c624db524e98d0
https://doi.org/10.3233/shti220714
https://doi.org/10.3233/shti220714
Autor:
Cedric, Bousquet, Diva, Beltramin
Publikováno v:
Studies in health technology and informatics. 294
In 2022, the Medical Informatics Europe conference created a special topic called "Challenges of trustable AI and added-value on health" which was centered around the theme of eXplainable Artificial Intelligence. Unfortunately, two opposite views rem
Autor:
T Trang, Nghiem, Cedric, Bousquet
Publikováno v:
Studies in health technology and informatics. 294
Methods of natural language processing associated with machine learning or deep learning can support detection of adverse drug reactions in abstracts of case reports available on Pubmed. In 2012, Gurulingappa et al. proposed a training set for the re
Autor:
T. Trang Nghiem, Cedric Bousquet
Methods of natural language processing associated with machine learning or deep learning can support detection of adverse drug reactions in abstracts of case reports available on Pubmed. In 2012, Gurulingappa et al. proposed a training set for the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b111a9363b87b75ea119bcb7f441d716
https://doi.org/10.3233/shti220615
https://doi.org/10.3233/shti220615
Autor:
Cedric Bousquet, Diva Beltramin
In 2022, the Medical Informatics Europe conference created a special topic called “Challenges of trustable AI and added-value on health” which was centered around the theme of eXplainable Artificial Intelligence. Unfortunately, two opposite views
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0050b73db7fb8e2e7cb33802240e56dd
https://doi.org/10.3233/shti220407
https://doi.org/10.3233/shti220407
BackgroundWithin a few months, the COVID-19 pandemic has spread to many countries and has been a real challenge for health systems all around the world. This unprecedented crisis has led to a surge of online discussions about potential cures for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0eb52ba61644a42d991526f1e7b343f
https://doi.org/10.1101/2022.02.14.22268832
https://doi.org/10.1101/2022.02.14.22268832
Autor:
Alexandre Dupuy-Zini, Bissan Audeh, Christel Gérardin, Catherine Duclos, Amandine Gagneux-Brunon, Cedric Bousquet
BACKGROUND Within a few months, the COVID-19 pandemic had spread to many countries and had been a real challenge for health systems all around the world. This unprecedented crisis has led to a surge of online discussions about potential cures for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef587c405e0037759e924391fdbc2c1e
https://doi.org/10.2196/preprints.37237
https://doi.org/10.2196/preprints.37237