Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Priyadip Ray"'
Autor:
Daniel H. Kwon, Jose Cadena, Sam Nguyen, Kwan Ho Ryan Chan, Braden Soper, Amy L. Gryshuk, Julian C. Hong, Priyadip Ray, Franklin W. Huang
Publikováno v:
Cancer Medicine, Vol 11, Iss 11, Pp 2204-2215 (2022)
Abstract Background The interaction between cancer diagnoses and COVID‐19 infection and outcomes is unclear. We leveraged a state‐wide, multi‐institutional database to assess cancer‐related risk factors for poor COVID‐19 outcomes. Methods W
Externí odkaz:
https://doaj.org/article/2720c0aad55e47dcaa8d0050cf24c713
Autor:
Sam Nguyen, Ryan Chan, Jose Cadena, Braden Soper, Paul Kiszka, Lucas Womack, Mark Work, Joan M. Duggan, Steven T. Haller, Jennifer A. Hanrahan, David J. Kennedy, Deepa Mukundan, Priyadip Ray
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract The combination of machine learning (ML) and electronic health records (EHR) data may be able to improve outcomes of hospitalized COVID-19 patients through improved risk stratification and patient outcome prediction. However, in resource con
Externí odkaz:
https://doaj.org/article/f84bcc357880499c918c1874c4e4b670
Publikováno v:
BMC Medical Research Methodology, Vol 20, Iss 1, Pp 1-40 (2020)
Abstract Background Machine learning (ML) has made a significant impact in medicine and cancer research; however, its impact in these areas has been undeniably slower and more limited than in other application domains. A major reason for this has bee
Externí odkaz:
https://doaj.org/article/e11559c49d904c0ebc01f5521fc62546
Autor:
Andre Goncalves, Braden Soper, Mari Nygård, Jan F Nygård, Priyadip Ray, David Widemann, Ana Paula Sales
Publikováno v:
PLoS ONE, Vol 15, Iss 11, p e0241225 (2020)
Oncology is a highly siloed field of research in which sub-disciplinary specialization has limited the amount of information shared between researchers of distinct cancer types. This can be attributed to legitimate differences in the physiology and c
Externí odkaz:
https://doaj.org/article/b9a2c3ac2e774665a54b29f3bb450bb9
Autor:
Priyadip Ray, Pramod K. Varshney
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 4, Iss 1, Pp 5-12 (2008)
Externí odkaz:
https://doaj.org/article/3a529e54bcf04703b13e6818bd690c93
Publikováno v:
IEEE Transactions on Signal Processing. 69:1713-1724
Distributed Bayesian inference provides a full quantification of uncertainty offering numerous advantages over point estimates that autonomous sensor networks are able to exploit. However, fully-decentralized Bayesian inference often requires large c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63c582108d8872227e0073e048f20207
https://doi.org/10.1109/tsp.2021.3058765
https://doi.org/10.1109/tsp.2021.3058765
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 67:1962-1975
Detection of a weak signal in additive Generalized Cauchy (GC) noise is important in many applications. The locally optimum detector (LOD) for a weak signal in GC noise is nonlinear in nature. When noise variance is unknown, the maximum likelihood es
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aed9c9580b3c28797e903cdf58dc246b
https://doi.org/10.1109/tcsi.2020.2969985
https://doi.org/10.1109/tcsi.2020.2969985
Autor:
Priyadip Ray, Jyoti Mansukhani
Publikováno v:
IEEE Transactions on Wireless Communications. 18:5500-5510
Multi-antenna technologies have been widely used in modern wireless communication systems to achieve diversity gain, spatial multiplexing gain, and better interference suppression. Beamforming has been considered as a potential candidate for throughp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7bb11735aaa5158c5bee0e6195a20ae8
https://doi.org/10.1109/twc.2019.2936839
https://doi.org/10.1109/twc.2019.2936839
Publikováno v:
2021 55th Asilomar Conference on Signals, Systems, and Computers.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa6efb49d4f2c2ce87312a94c6dbbe6c
https://doi.org/10.1109/ieeeconf53345.2021.9723409
https://doi.org/10.1109/ieeeconf53345.2021.9723409
Autor:
Braden C Soper, Jose Cadena, Sam Nguyen, Kwan Ho Ryan Chan, Paul Kiszka, Lucas Womack, Mark Work, Joan M Duggan, Steven T Haller, Jennifer A Hanrahan, David J Kennedy, Deepa Mukundan, Priyadip Ray
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA. 29(5)
Objective The study sought to investigate the disease state–dependent risk profiles of patient demographics and medical comorbidities associated with adverse outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Mater
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32e78463a414af3e8e06e05f601acf40
https://pubmed.ncbi.nlm.nih.gov/35137149
https://pubmed.ncbi.nlm.nih.gov/35137149