Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Everett Rush"'
Autor:
Everett Rush, Ozgur Ozmen, Minsu Kim, Erin Rush Ortegon, Makoto Jones, Byung H. Park, Steven Pizer, Jodie Trafton, Lisa A. Brenner, Merry Ward, Jonathan R. Nebeker
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background To discover pharmacotherapy prescription patterns and their statistical associations with outcomes through a clinical pathway inference framework applied to real-world data. Methods We apply machine learning steps in our framework
Externí odkaz:
https://doaj.org/article/1f66a97ac8ee4a47b13c4f8bfb608f21
Autor:
Chuan Hong, Everett Rush, Molei Liu, Doudou Zhou, Jiehuan Sun, Aaron Sonabend, Victor M. Castro, Petra Schubert, Vidul A. Panickan, Tianrun Cai, Lauren Costa, Zeling He, Nicholas Link, Ronald Hauser, J. Michael Gaziano, Shawn N. Murphy, George Ostrouchov, Yuk-Lam Ho, Edmon Begoli, Junwei Lu, Kelly Cho, Katherine P. Liao, Tianxi Cai, VA Million Veteran Program
Publikováno v:
npj Digital Medicine, Vol 4, Iss 1, Pp 1-11 (2021)
Abstract The increasing availability of electronic health record (EHR) systems has created enormous potential for translational research. However, it is difficult to know all the relevant codes related to a phenotype due to the large number of codes
Externí odkaz:
https://doaj.org/article/86da6cafdb7c469b8476bf57bfc46449
Autor:
Ziming Gan, Doudou Zhou, Everett Rush, Vidul A. Panickan, Yuk-Lam Ho, George Ostrouchov, Zhiwei Xu, Shuting Shen, Xin Xiong, Kimberly F. Greco, Chuan Hong, Clara-Lea Bonzel, Jun Wen, Lauren Costa, Tianrun Cai, Edmon Begoli, Zongqi Xia, J. Michael Gaziano, Katherine P. Liao, Kelly Cho, Tianxi Cai, Junwei Lu
Publikováno v:
medRxiv
SummaryObjectiveElectronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes, covering hundreds of thousands of clinical concepts available for research and clinical care. The com
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d52a320e26a595a900fa3b6bf0face50
https://doi.org/10.1101/2023.05.14.23289955
https://doi.org/10.1101/2023.05.14.23289955
Autor:
Jun Wen, Xiang Zhang, Everett Rush, Vidul A Panickan, Xingyu Li, Tianrun Cai, Doudou Zhou, Yuk-Lam Ho, Lauren Costa, Edmon Begoli, Chuan Hong, J Michael Gaziano, Kelly Cho, Junwei Lu, Katherine P Liao, Marinka Zitnik, Tianxi Cai
Publikováno v:
Bioinformatics. 39
MotivationPredicting molecule–disease indications and side effects is important for drug development and pharmacovigilance. Comprehensively mining molecule–molecule, molecule–disease and disease–disease semantic dependencies can potentially i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c329475e998de011e0548ebac2f844c
https://doi.org/10.1093/bioinformatics/btad085
https://doi.org/10.1093/bioinformatics/btad085
Autor:
Everett Rush, Ozgur Ozmen, Minsu Kim, Erin Ortegon, Makoto Jones, Byung Park, Steven Pizer, Jodie Trafton, Lisa A. Brenner, Merry Ward, Jonathan Nebeker
ObjectiveTo discover pharmacotherapy prescription patterns and their statistical associations with outcomes through a clinical pathway inference framework applied on real-world data.Materials and MethodsWe apply machine learning steps in our framewor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e398b1831e1251b8c7f5c41fb6593c5
https://doi.org/10.1101/2022.07.27.22277782
https://doi.org/10.1101/2022.07.27.22277782
Autor:
Doudou Zhou, Ziming Gan, Xu Shi, Alina Patwari, Everett Rush, Clara-Lea Bonzel, Vidul A. Panickan, Chuan Hong, Yuk-Lam Ho, Tianrun Cai, Lauren Costa, Xiaoou Li, Victor M. Castro, Shawn N. Murphy, Gabriel Brat, Griffin Weber, Paul Avillach, J. Michael Gaziano, Kelly Cho, Katherine P. Liao, Junwei Lu, Tianxi Cai
Publikováno v:
Journal of biomedical informatics. 133
The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interopera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac307e26f3cb5469e8678a9bc47879d8
https://pubmed.ncbi.nlm.nih.gov/35872266
https://pubmed.ncbi.nlm.nih.gov/35872266
Autor:
Junghoon Chae, Byung H. Park, Minsu Kim, Everett Rush, Ozgur Ozmen, Makoto Jones, Merry Ward, Jonathan R. Nebeker
Publikováno v:
Electronic Imaging. 35:395-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc5a7ed4d464a8a82cc31f2ecbba2b30
https://doi.org/10.2352/ei.2023.35.1.vda-395
https://doi.org/10.2352/ei.2023.35.1.vda-395
Autor:
Katherine P. Liao, Victor M. Castro, Junwei Lu, Ronald G. Hauser, Nicholas Link, George Ostrouchov, VA Million Veteran Program, Yuk-Lam Ho, Petra Schubert, Edmon Begoli, Tianxi Cai, Zeling He, Jiehuan Sun, Doudou Zhou, Chuan Hong, Vidul A. Panickan, Lauren Costa, Everett Rush, Kelly Cho, Molei Liu, Shawn N. Murphy, J. Michael Gaziano, Tianrun Cai, Aaron Sonabend
Publikováno v:
npj Digital Medicine, Vol 4, Iss 1, Pp 1-11 (2021)
NPJ Digital Medicine
NPJ Digital Medicine
The increasing availability of electronic health record (EHR) systems has created enormous potential for translational research. However, it is difficult to know all the relevant codes related to a phenotype due to the large number of codes available
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f1814fdc595d68b848bab751fe992b3
https://doi.org/10.1038/s41746-021-00519-z
https://doi.org/10.1038/s41746-021-00519-z
Publikováno v:
IEEE Transactions on Computers. 67:1840-1848
Disk I/O is a major bottleneck limiting the performance and scalability of data intensive applications. A common way to address disk I/O bottlenecks is using parallel storage systems and utilizing concurrent operation of independent storage component
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::305cd0385f94489bdbb8986599a4e4e6
https://doi.org/10.1109/tc.2018.2836426
https://doi.org/10.1109/tc.2018.2836426
Autor:
Ozgur Ozmen, Merry Ward, Byung H. Park, Makoto Jones, Everett Rush, Kathryn Knight, Jonathan R. Nebeker, Clifton R. Baker
Publikováno v:
CBMS
DOE / OSTI
DOE / OSTI
The process of identifying a cohort of interest is a very challenging task. It requires manually inspecting many patient records of complex structure that might include medical coding errors and missing data. This paper presents a computational pipel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::91dbce806f481a9361f2b751559032db
https://doi.org/10.1109/cbms49503.2020.00040
https://doi.org/10.1109/cbms49503.2020.00040