Department of Pediatrics, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin.
Division of Engineering Management, School of Systems and Enterprise, Stevens Institute of Technology, Hoboken, New Jersey.
Hosp Pediatr. 2022 Jan 1;12(1):93-110. doi: 10.1542/hpeds.2021-006094.
Artificial intelligence (AI) technologies are increasingly used in pediatrics and have the potential to help inpatient physicians provide high-quality care for critically ill children.
We aimed to describe the use of AI to improve any health outcome(s) in neonatal and pediatric intensive care.
PubMed, IEEE Xplore, Cochrane, and Web of Science databases.
We used peer-reviewed studies published between June 1, 2010, and May 31, 2020, in which researchers described (1) AI, (2) pediatrics, and (3) intensive care. Studies were included if researchers assessed AI use to improve at least 1 health outcome (eg, mortality).
Data extraction was conducted independently by 2 researchers. Articles were categorized by direct or indirect impact of AI, defined by the European Institute of Innovation and Technology Health joint report.
Of the 287 publications screened, 32 met inclusion criteria. Approximately 22% (n = 7) of studies revealed a direct impact and improvement in health outcomes after AI implementation. Majority were in prototype testing, and few were deployed into an ICU setting. Among the remaining 78% (n = 25) AI models outperformed standard clinical modalities and may have indirectly influenced patient outcomes. Quantitative assessment of health outcomes using statistical measures, such as area under the receiver operating curve (56%; n = 18) and specificity (38%; n = 12), revealed marked heterogeneity in metrics and standardization.
Few studies have revealed that AI has directly improved health outcomes for pediatric critical care patients. Further prospective, experimental studies are needed to assess AI's impact by using established implementation frameworks, standardized metrics, and validated outcome measures.
人工智能（AI）技术在儿科领域的应用日益广泛，有望帮助住院医师为危重症患儿提供高质量的医疗服务。
我们旨在描述 AI 在新生儿和儿科重症监护中改善任何健康结果的应用。
PubMed、IEEE Xplore、Cochrane 和 Web of Science 数据库。
我们使用了发表于 2010 年 6 月 1 日至 2020 年 5 月 31 日的同行评审研究，其中研究人员描述了（1）AI，（2）儿科学和（3）重症监护。如果研究人员评估了 AI 的使用以改善至少 1 项健康结果（例如死亡率），则将研究纳入研究范围。
数据提取由 2 名研究人员独立进行。文章按 AI 的直接或间接影响进行分类，由欧洲创新与技术研究所健康联合报告定义。
在筛选出的 287 篇论文中，有 32 篇符合纳入标准。大约 22%（n=7）的研究显示 AI 实施后对健康结果有直接影响和改善。大多数处于原型测试阶段，很少有部署到 ICU 环境中。其余 78%（n=25）的 AI 模型优于标准临床模式，可能间接地影响了患者的预后。使用统计措施（如接收者操作特征曲线下面积[56%；n=18]和特异性[38%；n=12]）对健康结果进行定量评估，发现指标和标准化存在显著的异质性。
很少有研究表明 AI 直接改善了儿科重症监护患者的健康结果。需要进一步前瞻性、实验性研究，使用既定的实施框架、标准化指标和经过验证的结果测量方法来评估 AI 的影响。
