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Article

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

Journal of biomedical informatics - 1 Feb 2020

Xu Zhenxing, Chou Jingyuan, Zhang Xi Sheryl, Luo Yuan, Isakova Tamara, Adekkanattu Prakash, Ancker Jessica S, Jiang Guoqian, Kiefer Richard C, Pacheco Jennifer A, Rasmussen Luke V, Pathak Jyotishman, Wang Fei

Abstract excerpt

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 large number of hospitalized patients. Accurate early prediction of AKI can enable in-time interventions and treatments. However, AKI is highly heterogeneous, thus identification of AKI sub-phenotypes can lead to an improved...

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PMID: 31911172
DOI: 10.1016/j.jbi.2019.103361

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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