Visual analytics of electronic health records with a focus on acute kidney injury
SS Abdullah - 2020 - search.proquest.com
The increasing use of electronic platforms in healthcare has resulted in the generation of
unprecedented amounts of data in recent years. The amount of data available to clinical …
unprecedented amounts of data in recent years. The amount of data available to clinical …
Internal and external validation of machine learning–assisted prediction models for mechanical ventilation–associated severe acute kidney injury
S Huang, Y Teng, J Du, X Zhou, F Duan, C Feng - Australian Critical Care, 2023 - Elsevier
Background Currently, very few preventive or therapeutic strategies are used for mechanical
ventilation (MV)-associated severe acute kidney injury (AKI). Objectives We developed …
ventilation (MV)-associated severe acute kidney injury (AKI). Objectives We developed …
An acute kidney injury prediction model based on ensemble learning algorithm
Acute Kidney Injury (AKI), a common disease in Intensive Care Unit (ICU) patients, is related
to high cost, morbidity and mortality. The early prediction of AKI is critical for improving …
to high cost, morbidity and mortality. The early prediction of AKI is critical for improving …
A Deep Learning Approach Incorporating Data Missing Mechanism in Predicting Acute Kidney Injury in ICU
Y Zhang, Z Zhang, X Liu, L Zha, Fengcong, X Su… - … on Intelligent Computing, 2023 - Springer
Abstract Acute Kidney Injury (AKI) is common in the intensive care units (ICUs) and is
associated with an increased risk of hospital mortality and additional healthcare-related …
associated with an increased risk of hospital mortality and additional healthcare-related …
Data Analysis of Impaired Renal and Cardiac Function Using a Combination of Standard Classifiers
We examine the significance of the predictive potential of EPI cystatin C (EPI CysC) in
combination with NTproBNP, sodium, and potassium in the evaluation of renal function in …
combination with NTproBNP, sodium, and potassium in the evaluation of renal function in …
A Review on Kidney Failure Prediction Using Machine Learning Models
BP Naveenya, J Premalatha - Reliability Engineering for Industrial …, 2024 - Springer
End-stage renal disease (ESRD), commonly known as kidney failure, is a critical medical
condition that has a significant impact on global health. Early detection of kidney failure is …
condition that has a significant impact on global health. Early detection of kidney failure is …
A machine learning model to predict diuretic resistance
JA Mercier, TW Ferguson, N Tangri - Kidney360, 2023 - journals.lww.com
Background Volume overload is a common complication encountered in hospitalized
patients, and the mainstay of therapy is diuresis. Unfortunately, the diuretic response in …
patients, and the mainstay of therapy is diuresis. Unfortunately, the diuretic response in …
Development and Validation of Transportable, Clinically Applicable and Scalable Machine Learning Models for Acute Kidney Injury
J Cao - 2024 - deepblue.lib.umich.edu
Acute kidney injury (AKI), a frequent complication in hospitalized patients, poses significant
challenges due to its high incidence, short-term mortality, and substantial economic burden …
challenges due to its high incidence, short-term mortality, and substantial economic burden …
Predicting Acute Kidney Injury: A Machine Learning Approach Using Electronic Health Records
Acute kidney injury (AKI) is a common complication in hospitalized patients and can result in
increased hospital stay, health-related costs, mortality and morbidity. A number of recent …
increased hospital stay, health-related costs, mortality and morbidity. A number of recent …
Early prediction of acquiring acute kidney injury for older inpatients using most effective laboratory test results
Abstract Background Acute Kidney Injury (AKI) is common among inpatients. Severe AKI
increases all-cause mortality especially in critically ill patients. Older patients are more at risk …
increases all-cause mortality especially in critically ill patients. Older patients are more at risk …