Artificial Intelligence in Acute Kidney Injury Risk Prediction

被引：42

作者：

Gameiro, Joana ^{[1
]}

Branco, Tiago ^{[2
]}

Lopes, Jose Antonio ^{[1
]}

机构：

[1] Ctr Hosp Lisboa Norte, Dept Med, Div Nephrol & Renal Transplantat, Av Prof Egas Moniz, P-1649035 Lisbon, Portugal

[2] Ctr Hosp Lisboa Norte, Dept Med, Av Prof Egas Moniz, P-1649035 Lisbon, Portugal

来源：

JOURNAL OF CLINICAL MEDICINE | 2020年 / 9卷 / 03期

关键词：

acute kidney injury; risk prediction; artificial intelligence; ACUTE-RENAL-FAILURE; CRITICALLY-ILL PATIENTS; GELATINASE-ASSOCIATED LIPOCALIN; RED-CELL STORAGE; CARDIAC-SURGERY; INDEPENDENT PREDICTOR; GLUCOSE-LEVELS; URIC-ACID; MORTALITY; AKI;

D O I：

10.3390/jcm9030678

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Acute kidney injury (AKI) is a frequent complication in hospitalized patients, which is associated with worse short and long-term outcomes. It is crucial to develop methods to identify patients at risk for AKI and to diagnose subclinical AKI in order to improve patient outcomes. The advances in clinical informatics and the increasing availability of electronic medical records have allowed for the development of artificial intelligence predictive models of risk estimation in AKI. In this review, we discussed the progress of AKI risk prediction from risk scores to electronic alerts to machine learning methods.

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页数：17

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