人工智能在急性肾损伤预测中的应用

IF 2 3区 医学 Q2 UROLOGY & NEPHROLOGY
Tushar Bajaj, Jay L. Koyner
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引用次数: 2

摘要

人工智能(AI)在肾脏病学及其相关临床研究中的应用越来越多。近年来,人们对利用人工智能预测医院急性肾损伤(AKI)的发展越来越感兴趣。已经采用了几种人工智能技术来提高在各种住院环境中检测AKI的能力。这篇综述讨论了AKI风险预测的演变,讨论了过去的静态风险评估模型以及最近人工智能和先进学习技术的趋势。我们讨论了AKI检测的相对改进,以及使用这些模型的临床实施和患者结果相关数据的相对缺乏。人工智能在AKI检测和临床护理中的应用尚处于起步阶段,本文描述了我们如何达到目前的地位,并暗示了未来的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence in Acute Kidney Injury Prediction

The use of artificial intelligence (AI) in nephrology and its associated clinical research is growing. Recent years have seen increased interest in utilizing AI to predict the development of hospital-based acute kidney injury (AKI). Several AI techniques have been employed to improve the ability to detect AKI across a variety of hospitalized settings. This review discusses the evolutions of AKI risk prediction discussing the static risk assessment models of yesteryear as well as the more recent trend toward AI and advanced learning techniques. We discuss the relative improvement in AKI detection as well as the relative dearth of data around the clinical implementation and patient outcomes using these models. The use of AI for AKI detection and clinical care is in its infancy, and this review describes how we arrived at our current position and hints at the promise of the future.

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来源期刊
Advances in chronic kidney disease
Advances in chronic kidney disease 医学-泌尿学与肾脏学
自引率
3.40%
发文量
69
审稿时长
11.1 weeks
期刊介绍: The purpose of Advances Chronic Kidney Disease is to provide in-depth, scholarly review articles about the care and management of persons with early kidney disease and kidney failure, as well as those at risk for kidney disease. Emphasis is on articles related to the early identification of kidney disease; prevention or delay in progression of kidney disease
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