[HTML][HTML] Real-time clinical decision support based on recurrent neural networks for in-hospital acute kidney injury: external validation and model interpretation
K Kim, H Yang, J Yi, HE Son, JY Ryu, YC Kim… - Journal of Medical …, 2021 - jmir.org
Background Acute kidney injury (AKI) is commonly encountered in clinical practice and is
associated with poor patient outcomes and increased health care costs. Despite it posing …
associated with poor patient outcomes and increased health care costs. Despite it posing …
[HTML][HTML] Multitask learning with recurrent neural networks for acute respiratory distress syndrome prediction using only electronic health record data: model …
Background Acute respiratory distress syndrome (ARDS) is a condition that is often
considered to have broad and subjective diagnostic criteria and is associated with …
considered to have broad and subjective diagnostic criteria and is associated with …
[HTML][HTML] Adult cardiac surgery-associated acute kidney injury: joint consensus report
Objectives Acute kidney injury (AKI) is increasingly recognized as a source of poor patient
outcomes after cardiac surgery. The purpose of the present report is to provide perioperative …
outcomes after cardiac surgery. The purpose of the present report is to provide perioperative …
The importance of the urinary output criterion for the detection and prognostic meaning of AKI
J Vanmassenhove, J Steen, S Vansteelandt… - Scientific Reports, 2021 - nature.com
Most reports on AKI claim to use KDIGO guidelines but fail to include the urinary output (UO)
criterion in their definition of AKI. We postulated that ignoring UO alters the incidence of AKI …
criterion in their definition of AKI. We postulated that ignoring UO alters the incidence of AKI …
机器学习在疾病预测的应用研究进展
刘雨安， 杨小文， 李乐之 - 护理学报, 2021 - manu68.magtech.com.cn
!"#$%&'()*+,-./0 Page 1 2021 年4 月 护理学报 April,2021 第28 卷第7 期Journal of Nursing(China)
Vol.28 No.7 [26] Cartwright J, Franklin D, Forman D, et al. Promoting Colr laborative …
Vol.28 No.7 [26] Cartwright J, Franklin D, Forman D, et al. Promoting Colr laborative …
[HTML][HTML] Evidence-based Clinical Decision Support Systems for the prediction and detection of three disease states in critical care: A systematic literature review
G Medic, MK Kließ, L Atallah, J Weichert, S Panda… - …, 2019 - ncbi.nlm.nih.gov
Background: Clinical decision support (CDS) systems have emerged as tools providing
intelligent decision making to address challenges of critical care. CDS systems can be …
intelligent decision making to address challenges of critical care. CDS systems can be …
[HTML][HTML] Convolutional neural network model for intensive care unit acute kidney injury prediction
S Le, A Allen, J Calvert, PM Palevsky, G Braden… - Kidney international …, 2021 - Elsevier
Introduction Acute kidney injury (AKI) is common among hospitalized patients and has a
significant impact on morbidity and mortality. Although early prediction of AKI has the …
significant impact on morbidity and mortality. Although early prediction of AKI has the …
A clinical, proteomics, and artificial intelligence‐driven model to predict acute kidney injury in patients undergoing coronary angiography
NE Ibrahim, CP McCarthy, S Shrestha… - Clinical …, 2019 - Wiley Online Library
Background Standard measures of kidney function are only modestly useful for accurate
prediction of risk for acute kidney injury (AKI). Hypothesis Clinical and biomarker data can …
prediction of risk for acute kidney injury (AKI). Hypothesis Clinical and biomarker data can …
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse …
H Burdick, E Pino, D Gabel-Comeau, C Gu… - BMC medical informatics …, 2020 - Springer
Background Severe sepsis and septic shock are among the leading causes of death in the
United States and sepsis remains one of the most expensive conditions to diagnose and …
United States and sepsis remains one of the most expensive conditions to diagnose and …
[HTML][HTML] Application of artificial intelligence in renal disease
L Yao, H Zhang, M Zhang, X Chen, J Zhang, J Huang… - Clinical eHealth, 2021 - Elsevier
Artificial intelligence (AI) has been applied widely in almost every area of our daily lives, due
to the growth of computing power, advances in methods and techniques, and the explosion …
to the growth of computing power, advances in methods and techniques, and the explosion …