建立并验证针对败血症儿童的人工智能预测模型。

IF 2.9 4区医学 Q3 IMMUNOLOGY

Pediatric Infectious Disease Journal Pub Date : 2024-08-01 Epub Date: 2024-05-08 DOI:10.1097/INF.0000000000004376

Li Wang, Yu-Hui Wu, Yong Ren, Fan-Fan Sun, Shao-Hua Tao, Hong-Xin Lin, Chuang-Sen Zhang, Wen Tang, Zhuang-Gui Chen, Chun Chen, Li-Dan Zhang

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引用次数: 0

摘要

背景：早期识别脓毒症患儿中的高危人群有利于降低脓毒症死亡率。本文利用人工智能（AI）技术有效、快速地预测了儿科重症监护病房（PICU）脓毒症患儿的死亡风险：这项回顾性观察研究于2016年12月至2019年6月在中山大学附属第一医院PICU进行，于2019年1月至2020年7月在深圳市儿童医院PICU进行。患儿被分为死亡组和存活组。采用不同的机器语言（ML）模型预测败血症患儿的死亡风险：结果：共招募了 671 名败血症患儿。人工神经网络模型的准确率（ACC）优于支持向量机、逻辑回归分析、贝叶斯、K 近邻法和决策树模型，训练集 ACC 为 0.99，测试集 ACC 为 0.96：人工智能模型可用于预测 PICU 儿童因败血症死亡的风险，人工神经网络模型在预测死亡风险方面优于其他人工智能模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Establishment and Verification of an Artificial Intelligence Prediction Model for Children With Sepsis.

Background: Early identification of high-risk groups of children with sepsis is beneficial to reduce sepsis mortality. This article used artificial intelligence (AI) technology to predict the risk of death effectively and quickly in children with sepsis in the pediatric intensive care unit (PICU).

Study design: This retrospective observational study was conducted in the PICUs of the First Affiliated Hospital of Sun Yat-sen University from December 2016 to June 2019 and Shenzhen Children's Hospital from January 2019 to July 2020. The children were divided into a death group and a survival group. Different machine language (ML) models were used to predict the risk of death in children with sepsis.

Results: A total of 671 children with sepsis were enrolled. The accuracy (ACC) of the artificial neural network model was better than that of support vector machine, logical regression analysis, Bayesian, K nearest neighbor method and decision tree models, with a training set ACC of 0.99 and a test set ACC of 0.96.

Conclusions: The AI model can be used to predict the risk of death due to sepsis in children in the PICU, and the artificial neural network model is better than other AI models in predicting mortality risk.

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来源期刊

Pediatric Infectious Disease Journal 医学-传染病学

CiteScore

6.30

自引率

2.80%

发文量

566

审稿时长

2-4 weeks

期刊介绍： The Pediatric Infectious Disease Journal® (PIDJ) is a complete, up-to-the-minute resource on infectious diseases in children. Through a mix of original studies, informative review articles, and unique case reports, PIDJ delivers the latest insights on combating disease in children — from state-of-the-art diagnostic techniques to the most effective drug therapies and other treatment protocols. It is a resource that can improve patient care and stimulate your personal research.