A clinically applicable approach to continuous prediction of future acute kidney injury

N Tomašev, X Glorot, JW Rae, M Zielinski, H Askham… - Nature, 2019 - nature.com
The early prediction of deterioration could have an important role in supporting healthcare
professionals, as an estimated 11% of deaths in hospital follow a failure to promptly …

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records

N Tomašev, N Harris, S Baur, A Mottram, X Glorot… - Nature …, 2021 - nature.com
Early prediction of patient outcomes is important for targeting preventive care. This protocol
describes a practical workflow for developing deep-learning risk models that can predict …

Utilizing Electronic Health Records to Predict Acute Kidney Injury Risk and Outcomes: Workgroup Statements from the 15th ADQI Consensus Conference

SM Sutherland, LS Chawla… - Canadian journal of …, 2016 - journals.sagepub.com
The data contained within the electronic health record (EHR) is “big” from the standpoint of
volume, velocity, and variety. These circumstances and the pervasive trend towards EHR …

[HTML][HTML] Scalable and accurate deep learning with electronic health records

A Rajkomar, E Oren, K Chen, AM Dai, N Hajaj… - NPJ digital …, 2018 - nature.com
Predictive modeling with electronic health record (EHR) data is anticipated to drive
personalized medicine and improve healthcare quality. Constructing predictive statistical …

[HTML][HTML] Deep-learning-based real-time prediction of acute kidney injury outperforms human predictive performance

N Rank, B Pfahringer, J Kempfert, C Stamm… - NPJ digital …, 2020 - nature.com
Acute kidney injury (AKI) is a major complication after cardiothoracic surgery. Early
prediction of AKI could prompt preventive measures, but is challenging in the clinical routine …

Generalizability of an acute kidney injury prediction model across health systems

J Cao, X Zhang, V Shahinian, H Yin, D Steffick… - Nature machine …, 2022 - nature.com
Delays in the identification of acute kidney injury in hospitalized patients are a major barrier
to the development of effective interventions for treatment. A recent study described a series …

[HTML][HTML] Identifying sub-phenotypes of acute kidney injury using structured and unstructured electronic health record data with memory networks

Z Xu, J Chou, XS Zhang, Y Luo, T Isakova… - Journal of biomedical …, 2020 - Elsevier
Abstract Acute Kidney Injury (AKI) is a common clinical syndrome characterized by the rapid
loss of kidney excretory function, which aggravates the clinical severity of other diseases in a …

[HTML][HTML] Predicting inpatient acute kidney injury over different time horizons: how early and accurate?

P Cheng, LR Waitman, Y Hu, M Liu - AMIA Annual Symposium …, 2017 - ncbi.nlm.nih.gov
Abstract 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 …

Derivation and external validation of prediction models for advanced chronic kidney disease following acute kidney injury

MT James, N Pannu, BR Hemmelgarn, PC Austin… - Jama, 2017 - jamanetwork.com
Importance Some patients will develop chronic kidney disease after a hospitalization with
acute kidney injury; however, no risk-prediction tools have been developed to identify high …

[HTML][HTML] A simple real-time model for predicting acute kidney injury in hospitalized patients in the US: a descriptive modeling study

M Simonov, U Ugwuowo, E Moreira, Y Yamamoto… - PLoS …, 2019 - journals.plos.org
Background Acute kidney injury (AKI) is an adverse event that carries significant morbidity.
Given that interventions after AKI occurrence have poor performance, there is substantial …