Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Malarkodi J. Samayamuthu"'
Autor:
Bertrand Moal, Arthur Orieux, Thomas Ferté, Antoine Neuraz, Gabriel A. Brat, Paul Avillach, Clara-Lea Bonzel, Tianxi Cai, Kelly Cho, Sébastien Cossin, Romain Griffier, David A. Hanauer, Christian Haverkamp, Yuk-Lam Ho, Chuan Hong, Meghan R. Hutch, Jeffrey G. Klann, Trang T. Le, Ne Hooi Will Loh, Yuan Luo, Adeline Makoudjou, Michele Morris, Danielle L. Mowery, Karen L. Olson, Lav P. Patel, Malarkodi J. Samayamuthu, Fernando J. Sanz Vidorreta, Emily R. Schriver, Petra Schubert, Guillaume Verdy, Shyam Visweswaran, Xuan Wang, Griffin M. Weber, Zongqi Xia, William Yuan, Harrison G. Zhang, Daniela Zöller, Isaac S. Kohane, The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Alexandre Boyer, Vianney Jouhet
Publikováno v:
PLoS ONE, Vol 18, Iss 1 (2023)
Purpose In young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of
Externí odkaz:
https://doaj.org/article/c2a2612d5d4c4f97828c5b687c3ea049
Autor:
Trang T. Le, Alba Gutiérrez-Sacristán, Jiyeon Son, Chuan Hong, Andrew M. South, Brett K. Beaulieu-Jones, Ne Hooi Will Loh, Yuan Luo, Michele Morris, Kee Yuan Ngiam, Lav P. Patel, Malarkodi J. Samayamuthu, Emily Schriver, Amelia L. M. Tan, Jason Moore, Tianxi Cai, Gilbert S. Omenn, Paul Avillach, Isaac S. Kohane, The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Shyam Visweswaran, Danielle L. Mowery, Zongqi Xia
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
Abstract Neurological complications worsen outcomes in COVID-19. To define the prevalence of neurological conditions among hospitalized patients with a positive SARS-CoV-2 reverse transcription polymerase chain reaction test in geographically diverse
Externí odkaz:
https://doaj.org/article/ee09dfbfb5e24e5d850dfff26a29ff64
Autor:
Michele I. Morris, Donglu Xie, Griffin M. Weber, Amy Chuang, Jeffrey G. Klann, Douglas MacFadden, Lee M. Nadler, Malarkodi J Samayamuthu, Philip Trevvett, Mark Abajian, Elaina R. Sendro, Wenhong Zhu, Amy Y. Wang, Gary S. Firestein, Nebojsa Mirkovic, Phillip Reeder, Robert W Follett, Robert D. Johnson, Shawn N. Murphy, Matthew C. Wyatt, Robert D Toto, Steven E. Reis, Shyam Visweswaran, Vivian S. Gainer, Lav P Patel, Neil Bahroos, Ngan Chau, Jennifer Cai, Barbara Benoit, Yuliya Borovskiy
Publikováno v:
JAMIA Open. 4
Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for
Publikováno v:
ACI open
Background Machine learning models that are used for predicting clinical outcomes can be made more useful by augmenting predictions with simple and reliable patient-specific explanations for each prediction. Objectives This article evaluates the qual
Autor:
Robert W Follett, Phillip Reeder, Amy Y. Wang, Nebojsa Mirkovic, Shawn N. Murphy, Shyam Visweswaran, Steven E. Reis, Elaina R. Sendro, Vivian S. Gainer, Gary S. Firestein, Douglas MacFadden, Lee M. Nadler, Wenhong Zhu, Philip Trevvett, Lav P Patel, Amy Chuang, Neil Bahroos, Michele I. Morris, Robert D. Toto, Ngan Chau, Donglu Xie, Robert D. Johnson, Jeffrey G. Klann, Malarkodi J Samayamuthu, Mark Abajian, Barbara Benoit, Yuliya Borovskiy, Griffin M. Weber, Matthew C. Wyatt, Jennifer Cai
Publikováno v:
JAMIA Open
medRxiv
article-version (status) pre
article-version (number) 1
medRxiv
article-version (status) pre
article-version (number) 1
Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::294eba3e3ee39bab1c6d2faaac5cc41b
https://doi.org/10.1101/2021.03.15.21253596
https://doi.org/10.1101/2021.03.15.21253596
Autor:
Ne Hooi Will Loh, Shawn N. Murphy, Bertrand Moal, Siegbert Rieg, Kenneth D. Mandl, Yuan Luo, Douglas S. Bell, Riccardo Bellazzi, Martin Boeker, Michele I. Morris, Alberto Malovini, Thomas Maulhardt, Victor Castro, Valentina Tibollo, Hossein Estiri, Shyam Visweswaran, Kavishwar B. Wagholikar, Vianney Jouhet, Anthony L L J Li, Amelia L.M. Tan, Kee Yuan Ngiam, Chuan Hong, Alon Geva, Andrew M South, Emily Schriver, Gabriel A. Brat, Griffin M. Weber, Danielle L. Mowery, David A. Hanauer, Meghan R Hutch, Zongqi Xia, Jason H. Moore, Robert W Follett, Jeffrey G. Klann, Malarkodi J Samayamuthu, Gilbert S. Omenn, Luca Chiovato, Karen L. Olson, Paul Avillach, Brett K. Beaulieu-Jones, Isaac S. Kohane
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association, BMJ Publishing Group, 2021, ⟨10.1093/jamia/ocab018⟩
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association, BMJ Publishing Group, 2021, ⟨10.1093/jamia/ocab018⟩
Objective The Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing coronavirus disease 2019 (COVID-19) with federated analyses of electronic health record (EHR) data. We sought to develop and
Autor:
Kee Yuan Ngiam, Michele I. Morris, Lav P Patel, Chuan Hong, Andrew M South, Trang T. Le, Emily Schriver, Jiyeon Son, Yuan Luo, Jason H. Moore, Zongqi Xia, Paul Avillach, Brett K Beaulieu-Jones, Shyam Visweswaran, Malarkodi J Samayamuthu, Tianxi Cai, Isaac S. Kohane, Amelia Lm Tan, Ne Hooi Will Loh, Gilbert S. Omenn, Danielle L. Mowery, Alba Gutiérrez-Sacristán
Publikováno v:
medRxiv
OBJECTIVENeurological complications can worsen outcomes in COVID-19. We defined the prevalence of a wide range of neurological conditions among patients hospitalized with COVID-19 in geographically diverse multinational populations.METHODSUsing elect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b62608efedf8231a303035c0f9a0c4fe
https://doi.org/10.1101/2021.01.27.21249817
https://doi.org/10.1101/2021.01.27.21249817
Autor:
Douglas S. Bell, Jeffrey G. Klann, Gilbert S. Omenn, Malarkodi J Samayamuthu, Alon Geva, Isaac S. Kohane, Karen L. Olson, Shyam Visweswaran, Alberto Malovini, Thomas Maulhardt, Brett K. Beaulieu-Jones, Gabriel A. Brat, Paul Avillach, Luca Chiovato, Chuan Hong, Zongqi Xia, Robert W Follett, Emilly Schriver, Danielle L. Mowery, Martin Boeker, Hossein Estiri, Kavishwar B. Wagholikar, Andrew M South, Bertrand Moal, Griffin M. Weber, Jason H. Moore, Siegbert Rieg, Riccardo Bellazzi, David A. Hanauer, Vianney Jouhet, Amelia Lm Tan, Anthony L L J Li, Kenneth D. Mandl, Ne Hooi Will Loh, Kee Yuan Ngiam, Valentina Tibollo, Shawn N. Murphy, Victor M. Castro, Michele I. Morris
IntroductionThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE) includes hundreds of hospitals internationally using a federated computational approach to COVID-19 research using the EHR.ObjectiveWe sought to develop and validate a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c39f781753591632333175858a2314a3
https://doi.org/10.1101/2020.10.13.20201855
https://doi.org/10.1101/2020.10.13.20201855