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Overview of clinical prediction models.

作者信息

Chen Lingxiao

机构信息

Institute of Bone and Joint Research, Kolling Institute, Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.

出版信息

Ann Transl Med. 2020 Feb;8(4):71. doi: 10.21037/atm.2019.11.121.

DOI:10.21037/atm.2019.11.121
PMID:32175364
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7049012/
Abstract
摘要

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本文引用的文献

1
In-depth mining of clinical data: the construction of clinical prediction model with R.临床数据的深度挖掘：使用R构建临床预测模型。
Ann Transl Med. 2019 Dec;7(23):796. doi: 10.21037/atm.2019.08.63.
2
RoB 2: a revised tool for assessing risk of bias in randomised trials.《随机对照试验偏倚风险评估工具2：修订版》
BMJ. 2019 Aug 28;366:l4898. doi: 10.1136/bmj.l4898.
3
Statistics versus machine learning: definitions are interesting (but understanding, methodology, and reporting are more important).统计学与机器学习：定义固然有趣（但理解、方法和报告更为重要）。
J Clin Epidemiol. 2019 Dec;116:137-138. doi: 10.1016/j.jclinepi.2019.08.002. Epub 2019 Aug 16.
4
The uncertainty with using risk prediction models for individual decision making: an exemplar cohort study examining the prediction of cardiovascular disease in English primary care.使用风险预测模型进行个体决策的不确定性：以英国初级保健中心血管疾病预测为例的队列研究
BMC Med. 2019 Jul 17;17(1):134. doi: 10.1186/s12916-019-1368-8.
5
When and how to use data from randomised trials to develop or validate prognostic models.何时以及如何使用随机试验数据来开发或验证预后模型。
BMJ. 2019 May 29;365:l2154. doi: 10.1136/bmj.l2154.
6
Reporting of artificial intelligence prediction models.人工智能预测模型的报告。
Lancet. 2019 Apr 20;393(10181):1577-1579. doi: 10.1016/S0140-6736(19)30037-6.
7
Guide to presenting clinical prediction models for use in clinical settings.临床环境中使用的临床预测模型呈现指南。
BMJ. 2019 Apr 17;365:l737. doi: 10.1136/bmj.l737.
8
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.系统评价显示，机器学习在临床预测模型中并未优于逻辑回归。
J Clin Epidemiol. 2019 Jun;110:12-22. doi: 10.1016/j.jclinepi.2019.02.004. Epub 2019 Feb 11.
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PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies.PROBAST：一种用于评估偏倚风险和预测模型研究适用性的工具。
Ann Intern Med. 2019 Jan 1;170(1):51-58. doi: 10.7326/M18-1376.
10
Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes.建立多变量预测模型的最小样本量：第二部分 - 二分类和生存数据。
Stat Med. 2019 Mar 30;38(7):1276-1296. doi: 10.1002/sim.7992. Epub 2018 Oct 24.