Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Omid Nohadani"'
Publikováno v:
Critical Care Explorations, Vol 5, Iss 10, p e0984 (2023)
IMPORTANCE:. Characterizing medical interventions delivered to ICU patients over time and their relationship to outcomes can help set expectations and inform decisions made by patients, clinicians, and health systems. OBJECTIVES:. To determine whethe
Externí odkaz:
https://doaj.org/article/2edb3645445040fe8795e3486092abc0
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:
Omid Nohadani
Publikováno v:
Artificial Intelligence in Radiation Therapy ISBN: 9780750333399
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::904e7c1fa6be0fd564108b1b897b84aa
https://doi.org/10.1088/978-0-7503-3339-9ch2
https://doi.org/10.1088/978-0-7503-3339-9ch2
Publikováno v:
Operations Research.
The paper by Han, Bandi, and Nohadani on “On Finite Adaptability in Two-Stage Distributionally Robust Optimization” studies finite adaptability with the goal to construct interpretable and easily implementable policies in the context of two-stage
Autor:
Omid Nohadani, Kartikey Sharma
Robust optimization methods have shown practical advantages in a wide range of decision-making applications under uncertainty. Recently, their efficacy has been extended to multiperiod settings. Current approaches model uncertainty either independent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70520d0a7865bb0f863bba0abe1dc579
Autor:
Dimitris Bertsimas, Omid Nohadani
Publikováno v:
INFORMS Journal on Computing. 31:445-458
In many applications, statistical estimators serve to derive conclusions from data, for example, in finance, medical decision making, and clinical trials. However, the conclusions are typically dependent on uncertainties in the data. We use robust op
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
Autor:
Luca Mingardi, Pankaj Sarin, Dirk Varelmann, Iván J. Núñez Gil, Vicente Estrada, Agni Orfanoudaki, Holly Wiberg, Omid Nohadani, Alison Borenstein, Carlos Macaya, Bartolomeo Stellato, Dimitris Bertsimas
Publikováno v:
Health Care Management Science
Springer US
Springer US
The COVID-19 pandemic has prompted an international effort to develop and repurpose medications and procedures to effectively combat the disease. Several groups have focused on the potential treatment utility of angiotensin-converting–enzyme inhibi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c54640c22f45ad9468220de138e161f7
https://doi.org/10.1101/2020.10.30.20223594
https://doi.org/10.1101/2020.10.30.20223594
Autor:
Alexandre Jacquillat, Bartolomeo Stellato, Michael Li, Ivan Paskov, Kimberly Villalobos Carballo, Hamza Tazi Bouardi, Dimitris Bertsimas, Driss Lahlou Kitane, Arthur Delarue, Omar Skali Lami, Leonard Boussioux, Cynthia Zeng, Agni Orfanoudaki, Jean Pauphilet, Holly Wiberg, Ryan Cory-Wright, Theodore Papalexopoulos, Vassilis Digalakis, Luca Mingardi, Galit Lukin, Omid Nohadani
Publikováno v:
Springer US
Health Care Management Science
Health Care Management Science
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c08d52eea024fcb82665c37886da49b4
Publikováno v:
European Journal of Operational Research. 268:231-242
Data Envelopment Analysis (DEA) is a nonparametric, data driven method to conduct relative performance measurements among a set of decision making units (DMUs). Efficiency scores are computed based on assessing input and output data for each DMU by m