| 国外基于机器学习的住院患者跌倒风险预测模型构建研究及其启示 |
| 修订日期：2023-03-08 点此下载全文 |
| 引用本文：任媛渊,丁福,付荣娟.国外基于机器学习的住院患者跌倒风险预测模型构建研究及其启示[J].医学信息学杂志,2023,44(10):63-67, 80 |
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| 基金项目:重庆市科卫联合医学科研项目(项目编号:2020MSXM024)；重庆医科大学智慧医学研究项目(项目编号:ZHYX202226)；重庆医科大学研究生智慧医学专项研发计划(项目编号:YJSZHYX202214)。 |
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| 中文摘要:目的/意义 分析国外基于机器学习构建住院患者跌倒风险预测模型的研究现状,为我国相关研究提供参考。方法/过程 检索PubMed和Web of Science数据库中2017—2022年基于机器学习构建住院患者跌倒风险预测模型的文献,从研究角度、数据来源、构建方法、模型验证等方面梳理分析文献。结果/结论 国外相关研究角度独特,数据海量、采集周期长,采用多种机器学习方法建模,且模型验证方法多样。国外同行经验可供我国护理研究者合理借鉴。 |
| 中文关键词:跌倒 机器学习 住院患者 风险预测模型 |
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| Study on the Construction of the Fall Risk Prediction Model for Inpatients Based on Machine Learning at Abroad and Its Enlightenments |
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| Abstract:Purpose/Significance To analyze the current situation of foreign research on constructing the fall risk prediction model for inpatients based on machine learning, and to provide references for relevant research in China. Method/Process Foreign literatures on the construction of the fall risk prediction model for inpatients based on machine learning from 2017 to 2022 are searched in PubMed and Web of Science databases, and the literatures are analyzed from the prospects of research perspectives, data sources, construction methods, model validation, etc. Result/Conclusion Relevant foreign researches have unique perspectives, massive data, long collection cycle, multiple machine learning methods for modeling and various model verification methods. The experience of foreign counterparts can be used for references by Chinese nursing researchers. |
| keywords:fall machine learning inpatients risk prediction model |
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