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Updated: Feb 28, 2026

An R-Based Landscape Validation of a Competing Risk Model
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An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

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在临床试验中用于现场风险预测的机器学习:开发,外部验证和在现场资格认证中的操作应用

Zhiwen Yang1

  • 1Development Operations, AstraZeneca Global R&D (China) Co., Ltd., 88 Xizang Road, Jing'an District, Shanghai 200085, China.

International journal of medical informatics
|February 25, 2026
PubMed
概括

一个新的机器学习工具准确地预测了罕见疾病的临床试验场所风险,如西氨基酸心肌病 (ATTR-CM). 这种健康信息学方法改善了地点的选择和资格,证明了在不同疾病中广泛的适用性.

关键词:
临床决策支持 临床决策支持外部验证的验证方法医疗信息学 医疗信息学机器学习是机器学习.基于风险的监测是基于风险的监测.网站资格验证 网站资格验证

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