May 18, 2023 · In this study, we developed a data- and outcome-driven deep-learning (DL) approach to identify and analyze AKI subphenotypes with prognostic and therapeutic ...
In this study, we developed a data- and outcome-driven deep-learning (DL) approach to identify and analyze AKI subphenotypes with prognostic and therapeutic ...
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Utilization of Deep Learning for Subphenotype Identification in ...
www.ncbi.nlm.nih.gov › PMC7646246
Oct 8, 2020 · Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep ...
Identifying acute kidney injury subphenotypes using an outcome-driven deep-learning approach · Advances in artificial intelligence and deep learning systems in ...
This study used a memory network-based deep learning approach to discover AKI sub-phenotypes using structured and unstructured electronic health record (EHR) ...
Apr 10, 2019 · This study used a memory network-based deep learning approach to discover AKI sub-phenotypes using structured and unstructured electronic ...
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Our approach identified three distinct sub-phenotypes: sub-phenotype I is with an average age of 63.03±17.25years, and is characterized by mild loss of kidney ...
Aug 10, 2023 · The deep learning models showed high potential in identifying patients at high risk of AKI earlier, which could provide information to guide personalized ...
We identified 4 distinct SPs of SA-pAKI with differing patient characteristics and outcomes. Early recognition of these SPs will allow for personalized ...
Nov 1, 2020 � We then used deep learning to utilize all available vital signs, laboratory measurements, and comorbidities to identify subphenotypes. Outcomes�...