Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Aaron Boussina"'
Autor:
Aaron Boussina, Lennart Langouche, Augustine C. Obirieze, Mridu Sinha, Hannah Mack, William Leineweber, April Aralar, David T. Pride, Todd P. Coleman, Stephanie I. Fraley
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-13 (2024)
Abstract Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic sc
Externí odkaz:
https://doaj.org/article/eb1d0820ec3b437381ca816a07969730
Autor:
Aaron Boussina, Supreeth P. Shashikumar, Atul Malhotra, Robert L. Owens, Robert El-Kareh, Christopher A. Longhurst, Kimberly Quintero, Allison Donahue, Theodore C. Chan, Shamim Nemati, Gabriel Wardi
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-9 (2024)
Abstract Sepsis remains a major cause of mortality and morbidity worldwide. Algorithms that assist with the early recognition of sepsis may improve outcomes, but relatively few studies have examined their impact on real-world patient outcomes. Our ob
Externí odkaz:
https://doaj.org/article/b461fc4226524012bf4fd58623c0aec8
Author Correction: Impact of a deep learning sepsis prediction model on quality of care and survival
Autor:
Aaron Boussina, Supreeth P. Shashikumar, Atul Malhotra, Robert L. Owens, Robert El-Kareh, Christopher A. Longhurst, Kimberly Quintero, Allison Donahue, Theodore C. Chan, Shamim Nemati, Gabriel Wardi
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-1 (2024)
Externí odkaz:
https://doaj.org/article/0b6e37246e354952898b6bcdf7917272
Autor:
Aaron Boussina, Gabriel Wardi, Supreeth Prajwal Shashikumar, Atul Malhotra, Kai Zheng, Shamim Nemati
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e45614 (2023)
BackgroundRecent attempts at clinical phenotyping for sepsis have shown promise in identifying groups of patients with distinct treatment responses. Nonetheless, the replicability and actionability of these phenotypes remain an issue because the pati
Externí odkaz:
https://doaj.org/article/c960db3151cd40aca34c2c1d6bc34ce6
Autor:
Haben H. Yhdego, Arshia Nayebnazar, Fatemeh Amrollahi, Aaron Boussina, Supreeth Shashikumar, Gabriel Wardi, Shamim Nemati
Predictive models have been suggested as potential tools for identifying highest risk patients for hospital readmissions, in order to improve care coordination and ultimately long-term patient outcomes. However, the accuracy of current predictive mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b59215c4b7e65660b8f6c9dcc7fc746
https://doi.org/10.1101/2023.04.10.23288371
https://doi.org/10.1101/2023.04.10.23288371
Sepsis is a major cause of morbidity and mortality worldwide, and is caused by bacterial infection in a majority of cases. However, fungal sepsis often carries a higher mortality rate both due to its prevalence in immunocompromised patients as well a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00e2457b928e4d4b387990085a863d61
https://doi.org/10.1101/2023.04.10.23288378
https://doi.org/10.1101/2023.04.10.23288378
Autor:
Aaron Boussina, Supreeth Shashikumar, Fatemeh Amrollahi, Hayden Pour, Michael Hogarth, Shamim Nemati
The deployment of predictive analytic algorithms that can safely and seamlessly integrate into existing healthcare workflows remains a significant challenge. Here, we present a scalable, cloud-based, fault-tolerant platform that is capable of extract
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8240ccce924d1f35d735346b41819755
https://doi.org/10.1101/2023.04.10.23288373
https://doi.org/10.1101/2023.04.10.23288373
BACKGROUND Recent attempts at clinical phenotyping for sepsis have shown promise in identifying groups of patients with distinct treatment responses. Nonetheless, the replicability and actionability of these phenotypes remains an issue since the pati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2cc8fd1f8c492aa30d8bc609a7346411
https://doi.org/10.2196/preprints.45614
https://doi.org/10.2196/preprints.45614
Publikováno v:
Journal of Medical Internet Research.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de7cc886724059ce2323ba89f22452eb
https://doi.org/10.2196/45614
https://doi.org/10.2196/45614
Inhibition of microbial sulfate reduction in a flow-through column system by (per)chlorate treatment
Autor:
Gary Anderson, Lauren M. Tom, Hans K. Carlson, Anna Engelbrektson, Yvette M. Piceno, Christopher G. Hubbard, Mark E. Conrad, Hayden Wong, Yong T. Jin, Aaron Boussina, John D. Coates
Publikováno v:
Frontiers in microbiology, vol 5, iss JUN
Frontiers in Microbiology, Vol 5 (2014)
Frontiers in Microbiology
Frontiers in Microbiology, Vol 5 (2014)
Frontiers in Microbiology
Microbial sulfate reduction is a primary cause of oil reservoir souring. Here we show that\ud amendment with chlorate or perchlorate [collectively (per)chlorate] potentially resolves\ud this issue. Triplicate packed columns inoculated with marine sed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee5917df73b3d480acdaa2daf248c03c
https://doi.org/10.3389/fmicb.2014.00315
https://doi.org/10.3389/fmicb.2014.00315