Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury

BACKGROUND AND OBJECTIVES: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We used the Medi...

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書誌詳細
出版年:Clin J Am Soc Nephrol
主要な著者: Chaudhary, Kumardeep, Vaid, Akhil, Duffy, Áine, Paranjpe, Ishan, Jaladanki, Suraj, Paranjpe, Manish, Johnson, Kipp, Gokhale, Avantee, Pattharanitima, Pattharawin, Chauhan, Kinsuk, O’Hagan, Ross, Van Vleck, Tielman, Coca, Steven G., Cooper, Richard, Glicksberg, Benjamin, Bottinger, Erwin P., Chan, Lili, Nadkarni, Girish N.
フォーマット: Artigo
言語:Inglês
出版事項: American Society of Nephrology 2020
主題:
Original Articles
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC7646246/
https://ncbi.nlm.nih.gov/pubmed/33033164
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.2215/CJN.09330819
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