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Acute Kidney Injury

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Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Burn critical care represents a high impact population that may benefit from artificial intelligence and machine learning (ML). Acute kidney injury (AKI) recognition in burn patients could be enhanced by ML. The goal of this study was to ...

Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care.

Critical care (London, England)
BACKGROUND AND OBJECTIVES: Excess fluid balance in acute kidney injury (AKI) may be harmful, and conversely, some patients may respond to fluid challenges. This study aimed to develop a prediction model that can be used to differentiate between volum...

Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Poor electronic medical record (EMR) usability is detrimental to both clinicians and patients. A better EMR would provide concise, context sensitive patient data, but doing so entails the difficult task of knowing which data are relevant. To determin...

Ultra-high-performance liquid chromatography-mass spectrometry method for neutrophil gelatinase-associated lipocalin as a predictive biomarker in acute kidney injury.

Talanta
Neutrophil gelatinase associated lipocalin (NGAL) is a protein that was found to be overexpressed in acute kidney injury (AKI). The rise in NGAL concentration, both in urine or plasma, appears earlier than for other classical renal function markers s...

Artificial neural network algorithm model as powerful tool to predict acute lung injury following to severe acute pancreatitis.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
OBJECTIVE: The aim of this study is to predict the risk of severe acute pancreatitis (SAP) associated with acute lung injury (ALI) by artificial neural networks (ANNs) model.

Granulomatosis with polyangiitis in Northeastern Brazil: study of 25 cases and review of the literature.

Advances in rheumatology (London, England)
BACKGROUND: Little has been published about the epidemiology of Granulomatosis with polyangiitis (GPA) in South America, especially in the intertropical zone, and no epidemiological data from Brazil are available. The purpose of the present study was...

Predicting Inpatient Acute Kidney Injury over Different Time Horizons: How Early and Accurate?

AMIA ... Annual Symposium proceedings. AMIA Symposium
Incidence of Acute Kidney Injury (AKI) has increased dramatically over the past two decades due to rising prevalence of comorbidities and broadening repertoire of nephrotoxic medications. Hospitalized patients with AKI are at higher risk for complica...

Causal risk factor discovery for severe acute kidney injury using electronic health records.

BMC medical informatics and decision making
BACKGROUND: Acute kidney injury (AKI), characterized by abrupt deterioration of renal function, is a common clinical event among hospitalized patients and it is associated with high morbidity and mortality. AKI is defined in three stages with stage-3...