A deep-learning model to continuously predict severe acute kidney injury based on urine output changes in critically ill patients

Long-Term Outcomes in Patients with Acute Kidney Injury

(2020) Rebecca A. Noble et al.   Clinical Journal of the American Society of Nephrology

Artificial Intelligence in Acute Kidney Injury Risk Prediction

(2020) Joana Gameiro et al.   Journal of Clinical Medicine

Development and testing of an artificial intelligence tool for predicting end stage kidney disease in patients with immunoglobulin A nephropathy.

(2020) Francesco Paolo Schena et al.   KIDNEY INTERNATIONAL

Deep learning for time series classification: a review

(2019) Hassan Ismail Fawaz et al.   DATA MINING AND KNOWLEDGE DISCOVERY

Early prediction of acute kidney injury following ICU admission using a multivariate panel of physiological measurements

(2019) Lindsay P. Zimmerman et al.   BMC Medical Informatics and Decision Making

Electronic Alerts for Acute Kidney Injury Amelioration (ELAIA-1): a completely electronic, multicentre, randomised controlled trial: design and rationale

(2019) Marina Mutter et al.   BMJ Open

Changes in acute kidney injury epidemiology in critically ill patients: a population-based cohort study in Korea

(2019) Subin Hwang et al.   Annals of Intensive Care

Impact of Electronic Acute Kidney Injury (AKI) Alerts With Automated Nephrologist Consultation on Detection and Severity of AKI: A Quality Improvement Study

(2018) Sehoon Park et al.   AMERICAN JOURNAL OF KIDNEY DISEASES

Value of electronic alerts for acute kidney injury in high-risk wards: a pilot randomized controlled trial

(2018) Yanhua Wu et al.   INTERNATIONAL UROLOGY AND NEPHROLOGY

AKIpredictor, an online prognostic calculator for acute kidney injury in adult critically ill patients: development, validation and comparison to serum neutrophil gelatinase-associated lipocalin

(2017) Marine Flechet et al.   INTENSIVE CARE MEDICINE

Post-discharge kidney function is associated with subsequent ten-year renal progression risk among survivors of acute kidney injury

(2017) Simon Sawhney et al.   KIDNEY INTERNATIONAL

Incidence, timing and outcome of AKI in critically ill patients varies with the definition used and the addition of urine output criteria

(2017) J. Koeze et al.   BMC Nephrology

Universal equation for estimating ideal body weight and body weight at any BMI

(2016) Courtney M Peterson et al.   AMERICAN JOURNAL OF CLINICAL NUTRITION

Association of oliguria with the development of acute kidney injury in the critically ill

(2016) Suvi T. Vaara et al.   KIDNEY INTERNATIONAL

MIMIC-III, a freely accessible critical care database

(2016) Alistair E.W. Johnson et al.   Scientific Data

Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study

(2015) Eric A. J. Hoste et al.   INTENSIVE CARE MEDICINE

Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial

(2015) F Perry Wilson et al.   LANCET

International Society of Nephrology's 0by25 initiative for acute kidney injury (zero preventable deaths by 2025): a human rights case for nephrology

(2015) Ravindra L Mehta et al.   LANCET

Improving outcomes in patients with Acute Kidney Injury: the impact of hospital based automated AKI alerts

(2015) M Prendecki et al.   POSTGRADUATE MEDICAL JOURNAL

Electronic alerts for acute kidney injury

(2013) Nicholas M. Selby   CURRENT OPINION IN NEPHROLOGY AND HYPERTENSION

Incidence, risk factors and 90-day mortality of patients with acute kidney injury in Finnish intensive care units: the FINNAKI study

(2013) Sara Nisula et al.   INTENSIVE CARE MEDICINE

Temporal Changes in Incidence of Dialysis-Requiring AKI

(2012) R. K. Hsu et al.   JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY

Summary of Recommendation Statements

(2012)   Kidney International Supplements

Impact of real-time electronic alerting of acute kidney injury on therapeutic intervention and progression of RIFLE class*

(2011) Kirsten Colpaert et al.   CRITICAL CARE MEDICINE

Oliguria is an early predictor of higher mortality in critically ill patients

(2011) Etienne Macedo et al.   KIDNEY INTERNATIONAL

Intensity of Renal Support in Critically Ill Patients with Acute Kidney Injury

(2008)   NEW ENGLAND JOURNAL OF MEDICINE