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Tactical Size Unit as Distribution in a Data Farming Environment
Axioms, 2016-03, Vol.5 (1), p.7
2016
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An approximative method of simulating a duel
Proceedings of the 2012 Winter Simulation Conference (WSC), 2012, p.1-10
2012
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Effects of terrain in computational methods for indirect fire
Proceedings of the 2012 Winter Simulation Conference (WSC), 2012, p.1-12
2012
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Validating indirect fire models with field experiments : Verification, Validation, and Accreditation in Modeling & Simulation
Journal of defense modeling and simulation, 2013, Vol.10 (4), p.425-434
2013
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Validating indirect fire models with field experiments
Journal of defense modeling and simulation, 2013-10, Vol.10 (4), p.425-434
2013
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Direct Fire Target Selection in Sandis Combat Simulation
IFAC Proceedings Volumes, 2009, Vol.42 (2), p.242-245
2009
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Fluid overload is associated with an increased risk for 90-day mortality in critically ill patients with renal replacement therapy: data from the prospective FINNAKI study
Critical care (London, England), 2012-10, Vol.16 (5), p.R197-R197
2012
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Urinary cell cycle arrest biomarkers and chitinase 3-like protein 1 (CHI3L1) to detect acute kidney injury in the critically ill: a post hoc laboratory analysis on the FINNAKI cohort
Critical care (London, England), 2020-04, Vol.24 (1), p.144-10, Article 144
2020
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Heme oxygenase-1 repeat polymorphism in septic acute kidney injury
PloS one, 2019-05, Vol.14 (5), p.e0217291-e0217291
2019
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Predictive value of urine interleukin-18 in the evolution and outcome of acute kidney injury in critically ill adult patients
British journal of anaesthesia : BJA, 2015-03, Vol.114 (3), p.460-468
2015
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Urine NGAL as a biomarker for septic AKI: a critical appraisal of clinical utility—data from the observational FINNAKI study
Annals of intensive care, 2020-04, Vol.10 (1), p.51-51, Article 51
2020
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Genetic variants in SERPINA4 and SERPINA5, but not BCL2 and SIK3 are associated with acute kidney injury in critically ill patients with septic shock
Critical care (London, England), 2017-03, Vol.21 (1), p.47-47, Article 47
2017
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Six-month survival and quality of life of intensive care patients with acute kidney injury
Critical care (London, England), 2013-10, Vol.17 (5), p.R250-R250
2013
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Urinary Biomarkers Indicative of Apoptosis and Acute Kidney Injury in the Critically Ill
PloS one, 2016-02, Vol.11 (2), p.e0149956-e0149956
2016
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Predicting one-year mortality of critically ill patients with early acute kidney injury: data from the prospective multicenter FINNAKI study
Critical care (London, England), 2015-03, Vol.19 (1), p.125-125, Article 125
2015
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The Urine Protein NGAL Predicts Renal Replacement Therapy, but Not Acute Kidney Injury or 90-Day Mortality in Critically Ill Adult Patients
Anesthesia and analgesia, 2014-07, Vol.119 (1), p.95-102
2014
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Soluble CD73 in Critically Ill Septic Patients - Data from the Prospective FINNAKI Study
PloS one, 2016-10, Vol.11 (10), p.e0164420-e0164420
2016
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Variation in the use of renal replacement therapy in patients with septic shock: a substudy of the prospective multicenter observational FINNAKI study
Critical care (London, England), 2014-02, Vol.18 (1), p.R26-R26
2014
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Age of red blood cells and outcome in acute kidney injury
Critical care (London, England), 2013-10, Vol.17 (5), p.R222-R222
2013
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Three-year mortality in 30-day survivors of critical care with acute kidney injury: data from the prospective observational FINNAKI study
Annals of intensive care, 2016-11, Vol.6 (1), p.118-118, Article 118
2016
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Common Inflammation-Related Candidate Gene Variants and Acute Kidney Injury in 2647 Critically Ill Finnish Patients
Journal of clinical medicine, 2019-03, Vol.8 (3), p.342
2019
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Capítulo 4 - Fuentes de datos y vigilancia
Epidemiología y Bioestadística. Secretos, p.59-77
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Colaboradores
Epidemiología y Bioestadística. Secretos, p.vii-viii
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