Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Konstantina Palla"'
Autor:
Pratik Ghosh, Karen L. Posner, Stephanie L. Hyland, Wil Van Cleve, Melissa Bristow, Dustin R. Long, Konstantina Palla, Bala Nair, Christine Fong, Ronald Pauldine, Monica S. Vavilala, Kenton O'Hara
Publikováno v:
ACM Transactions on Computer-Human Interaction.
Hypotension during perioperative care, if undetected or uncontrolled, can lead to serious clinical complications. Predictive machine learning models, based on routinely collected EHR data, offer potential for early warning of hypotension to enable pr
Autor:
Konstantina Palla, Stephanie L. Hyland, Karen Posner, Pratik Ghosh, Bala Nair, Melissa Bristow, Yoana Paleva, Ben Williams, Christine Fong, Wil Van Cleve, Dustin R. Long, Ronald Pauldine, Kenton O'Hara, Kenji Takeda, Monica S. Vavilala
Publikováno v:
Br J Anaesth
BACKGROUND: Postoperative hypotension is associated with adverse outcomes, but intraoperative prediction of postanaesthesia care unit (PACU) hypotension is not routine in anaesthesiology workflow. Although machine learning models may support clinicia
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 37:462-474
Latent variable models for network data extract a summary of the relational structure underlying an observed network. The simplest possible models subdivide nodes of the network into clusters; the probability of a link between any two nodes then depe
Publikováno v:
IEEE Conference on Intelligence and Security Informatics (ISI), 2016
ISI
ISI
The possibility for theft or misuse of legitimate user credentials is a potential cyber-security weakness in any enterprise computer network which is almost impossible to eradicate. However, by monitoring the network traffic patterns, it can be possi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::324278d002f5fe75c740be3508a4a76e
http://hdl.handle.net/10044/1/42760
http://hdl.handle.net/10044/1/42760
Autor:
Zoubin Ghahramani, Gjergji Kasneci, Simon Lacoste-Julien, Alex Davies, Thore Graepel, Konstantina Palla
Publikováno v:
KDD 2013-The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
KDD 2013-The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug 2013, Chicago, United States. pp.572-580, ⟨10.1145/2487575.2487592⟩
KDD
KDD 2013-The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug 2013, Chicago, United States. pp.572-580, ⟨10.1145/2487575.2487592⟩
KDD
The Internet has enabled the creation of a growing number of large-scale knowledge bases in a variety of domains containing complementary information. Tools for automatically aligning these knowledge bases would make it possible to unify many sources
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::979cce76f4f26a8967cef17af00c68ea
https://hal.inria.fr/hal-00918671/file/fp0172-Lacoste-Julien.pdf
https://hal.inria.fr/hal-00918671/file/fp0172-Lacoste-Julien.pdf
Publikováno v:
MDM
We present a simulation environment that can be employed to study P2P mobile networks that are fast-evolving in both their topology and their content. This simulator implements a proposed P2P architecture based on Mobile Agent and Active Database tec