Zobrazeno 1 - 10 of 118 pro vyhledávání: '"Panos Pardalos"'
1
Report
Uniformly most powerful unbiased test for conditional independence in Gaussian graphical model
Autor: Petr, Koldanov, Alexander, Koldanov, Valeriy, Kalyagin, Panos, Pardalos
Model selection for Gaussian concentration graph is based on multiple testing of pairwise conditional independence. In practical applications partial correlation tests are widely used. However it is not known whether partial correlation test is unifo
Externí odkaz: http://arxiv.org/abs/1610.00316
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3
Akademický článek
Association of persistent acute kidney injury and renal recovery with mortality in hospitalised patients
Autor: Tyler J Loftus, Tezcan Ozrazgat-Baslanti, Azra Bihorac, Mark S Segal, Rajesh Mohandas, Yuanfang Ren, Esra Adiyeke, Shunshun Miao, Haleh Hashemighouchani, Rubab Islam, Saraswathi Gopal, Elizabeth A Shenkman, Panos Pardalos, Babette Brumback
Publikováno v: BMJ Health & Care Informatics, Vol 28, Iss 1 (2021)
Objectives Acute kidney injury (AKI) affects up to one-quarter of hospitalised patients and 60% of patients in the intensive care unit (ICU). We aim to understand the baseline characteristics of patients who will develop distinct AKI trajectories, de
Externí odkaz: https://doaj.org/article/8ce52d5ae223451fad6b557aa23d3b71
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4
Akademický článek
Why Farmers Get Involved in Participatory Research Projects? The Case of Arable Crops Farmers in Greece
Autor: George Vlontzos, Spyros Niavis, Christina Kleisiari, Leonidas Sotirios Kyrgiakos, Christos Athanassiou, Panos Pardalos
Publikováno v: Applied Sciences, Vol 11, Iss 1, p 6 (2020)
This paper seeks to underline the driving factors of farmers’ engagement in Participatory Research Projects (PRPs). This is a critical issue for formulating efficient and effective technology transfer channels, essential for improving the operation
Externí odkaz: https://doaj.org/article/6d7e38ce3e2c4063a11416c44fef6267
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6
Akademický článek
Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications.
Autor: Paul Thottakkara, Tezcan Ozrazgat-Baslanti, Bradley B Hupf, Parisa Rashidi, Panos Pardalos, Petar Momcilovic, Azra Bihorac
Publikováno v: PLoS ONE, Vol 11, Iss 5, p e0155705 (2016)
OBJECTIVE:To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN:Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010. PATIENTS:50,318 adult
Externí odkaz: https://doaj.org/article/477d5ef23b9c49179aff8f870a9f3fd6
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