人工智能在急性肾损伤风险预测中的应用
Artificial Intelligence in Acute Kidney Injury Risk Prediction.
作者信息
Gameiro Joana, Branco Tiago, Lopes José António
机构信息
Division of Nephrology and Renal Transplantation, Department of Medicine, Centro Hospitalar Lisboa Norte, EPE, Av. Prof. Egas Moniz, 1649-035 Lisboa, Portugal.
Department of Medicine, Centro Hospitalar Lisboa Norte, EPE, Av. Prof. Egas Moniz, 1649-035 Lisboa, Portugal.
出版信息
J Clin Med. 2020 Mar 3;9(3):678. doi: 10.3390/jcm9030678.
Abstract
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.
摘要
急性肾损伤（AKI）是住院患者常见的并发症，与短期和长期预后较差相关。开发识别AKI风险患者和诊断亚临床AKI的方法对于改善患者预后至关重要。临床信息学的进展以及电子病历可用性的提高使得AKI风险评估的人工智能预测模型得以发展。在本综述中，我们讨论了从风险评分到电子警报再到机器学习方法的AKI风险预测进展。
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