Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Agni Orfanoudaki"'
Autor:
Matthew I Miller, Agni Orfanoudaki, Benjamin Brush, Hanife Saglam, Oluwafemi Balogun, Maria Tzalidi, Kyriakos Vasilopoulos, Georgia Fanaropoulou, Nina Fanaropoulou, Michael Cronin, David Greer, Stelios Smirnakis, Charlene Ong
Publikováno v:
Stroke: Vascular and Interventional Neurology, Vol 1, Iss S1 (2021)
Introduction: Automated processing of electronic health data to classify complications of ischemic stroke serves numerous purposes, including improved electronic phenotyping for clinical research. Here, we present a natural language processing (NLP)
Externí odkaz:
https://doaj.org/article/4a97313f96024a199f307ba1b2db13a3
Autor:
Agni Orfanoudaki, Emma Chesley, Christian Cadisch, Barry Stein, Amre Nouh, Mark J Alberts, Dimitris Bertsimas
Publikováno v:
PLoS ONE, Vol 15, Iss 5, p e0232414 (2020)
Current stroke risk assessment tools presume the impact of risk factors is linear and cumulative. However, both novel risk factors and their interplay influencing stroke incidence are difficult to reveal using traditional additive models. The goal of
Externí odkaz:
https://doaj.org/article/55b9c39fd61b4b6cacb34739bf88e82a
Autor:
Charlene Jennifer Ong, Agni Orfanoudaki, Rebecca Zhang, Francois Pierre M Caprasse, Meghan Hutch, Liang Ma, Darian Fard, Oluwafemi Balogun, Matthew I Miller, Margaret Minnig, Hanife Saglam, Brenton Prescott, David M Greer, Stelios Smirnakis, Dimitris Bertsimas
Publikováno v:
PLoS ONE, Vol 15, Iss 6, p e0234908 (2020)
Accurate, automated extraction of clinical stroke information from unstructured text has several important applications. ICD-9/10 codes can misclassify ischemic stroke events and do not distinguish acuity or location. Expeditious, accurate data extra
Externí odkaz:
https://doaj.org/article/72e7c7ef072e49d58a4585794311a546
Autor:
Dimitris Bertsimas, Galit Lukin, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Bartolomeo Stellato, Holly Wiberg, Sara Gonzalez-Garcia, Carlos Luis Parra-Calderón, Kenneth Robinson, Michelle Schneider, Barry Stein, Alberto Estirado, Lia A Beccara, Rosario Canino, Martina Dal Bello, Federica Pezzetti, Angelo Pan, Hellenic COVID-19 Study Group
Publikováno v:
PLoS ONE, Vol 15, Iss 12, p e0243262 (2020)
Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator
Externí odkaz:
https://doaj.org/article/62d049f642ac421788c0226efb33be0d
Autor:
Agni Orfanoudaki, Joseph A. Dearani, David M. Shahian, Vinay Badhwar, Felix Fernandez, Robert Habib, Michael E. Bowdish, Dimitris Bertsimas
Publikováno v:
The Annals of Thoracic Surgery. 114:1995-2000
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::433914e59f0798dc9aaa02ca92137e0b
https://doi.org/10.1016/j.athoracsur.2022.06.058
https://doi.org/10.1016/j.athoracsur.2022.06.058
Publikováno v:
Naval Research Logistics (NRL). 69:669-688
Due to its prevalence and association with cardiovascular diseases and premature death, hypertension is a major public health challenge. Proper prevention and management measures are needed to effectively reduce the pervasiveness of the condition. Cu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5bda9e4303cfc394d24d999a872b6e5
https://doi.org/10.1002/nav.22040
https://doi.org/10.1002/nav.22040
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b40bffe3b79527572e36bbccd4d1c58
https://doi.org/10.2139/ssrn.4302002
https://doi.org/10.2139/ssrn.4302002
Autor:
Aikaterini Giannoutsou, Sabet W. Hashim, Dimitris Bertsimas, Robert C Hagberg, Agni Orfanoudaki
Publikováno v:
Journal of cardiac surgeryREFERENCES. 37(1)
Background Current Society of Thoracic Surgeons (STS) risk models for predicting outcomes of mitral valve surgery (MVS) assume a linear and cumulative impact of variables. We evaluated postoperative MVS outcomes and designed mortality and morbidity r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ec11a096cbf40a892a8d500ca3e0e60
https://pubmed.ncbi.nlm.nih.gov/34669218
https://pubmed.ncbi.nlm.nih.gov/34669218
Autor:
Angelo Pan, José Miguel Cisneros-Herreros, Luca Mingardi, Barry Stein, Alberto Estirado, Ken Robinson, Federica Pezzetti, Dimitris Bertsimas, Martina Dal Bello, Lia a Beccara, Carlos Luis Parra-Calderón, Michelle Schneider, Galit Lukin, Sara González-García, Holly Wiberg, Bartolomeo Stellato, Rosario Canino, Agni Orfanoudaki, Omid Nohadani
Publikováno v:
PLoS ONE
Digital.CSIC. Repositorio Institucional del CSIC
instname
PLoS ONE, Vol 15, Iss 12, p e0243262 (2020)
Digital.CSIC. Repositorio Institucional del CSIC
instname
PLoS ONE, Vol 15, Iss 12, p e0243262 (2020)
Background: Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7883c0da09060871f33f4033ff81673
http://hdl.handle.net/10261/225807
http://hdl.handle.net/10261/225807
Publikováno v:
Springer US
Missing data is a common problem in real-world settings and particularly relevant in healthcare applications where researchers use Electronic Health Records (EHR) and results of observational studies to apply analytics methods. This issue becomes eve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7e8abddda9e9bc25ba70d27a832c893
https://hdl.handle.net/1721.1/131956
https://hdl.handle.net/1721.1/131956