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Updated: Jun 6, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Establishing a Competing Risk Regression Nomogram Model for Survival Data

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使用生存分析的医疗住院患者住院时间的决定因素

Jaekyeong Kim1,2, Haegak Chang1, Seiyoung Ryu2

  • 1School of Management, Kyung Hee University, Seoul 02447, Republic of Korea.

International journal of environmental research and public health
|November 27, 2024
PubMed
概括

管理住院时间 (LOS) 对医疗保健费用至关重要. 这项研究使用了韩国大型数据集的生存分析,发现年龄,保险类型和医院类型显著影响LOS,告知资源管理.

关键词:
考克斯的比例危险模型.卡普兰·梅耶尔的生存分析.健康检查队列 DB DB停留时间的长度.医疗数据 医疗数据生存分析,生存分析.

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Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
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