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本文引用的文献

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Recommendations for Reporting Machine Learning Analyses in Clinical Research.机器学习分析在临床研究中的报告建议。
Circ Cardiovasc Qual Outcomes. 2020 Oct;13(10):e006556. doi: 10.1161/CIRCOUTCOMES.120.006556. Epub 2020 Oct 14.
2
Use of electronic medical records in development and validation of risk prediction models of hospital readmission: systematic review.电子病历在医院再入院风险预测模型的开发和验证中的应用：系统评价。
BMJ. 2020 Apr 8;369:m958. doi: 10.1136/bmj.m958.
3
Calculating the sample size required for developing a clinical prediction model.计算开发临床预测模型所需的样本量。
BMJ. 2020 Mar 18;368:m441. doi: 10.1136/bmj.m441.
4
Dissecting racial bias in an algorithm used to manage the health of populations.剖析用于管理人群健康的算法中的种族偏见。
Science. 2019 Oct 25;366(6464):447-453. doi: 10.1126/science.aax2342.
5
Extension of the CONSORT and SPIRIT statements.CONSORT和SPIRIT声明的扩展。
Lancet. 2019 Oct 5;394(10205):1225. doi: 10.1016/S0140-6736(19)31819-7. Epub 2019 Sep 16.
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
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.
8
Development and Validation of an Electronic Health Record-Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment.基于电子病历的机器学习模型开发与验证：用于预测无已知认知障碍的新入院患者发生谵妄的风险。
JAMA Netw Open. 2018 Aug 3;1(4):e181018. doi: 10.1001/jamanetworkopen.2018.1018.
9
Guidelines for reinforcement learning in healthcare.医疗保健领域强化学习指南。
Nat Med. 2019 Jan;25(1):16-18. doi: 10.1038/s41591-018-0310-5.
10
The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care.人工智能临床医生学习重症监护中脓毒症的最佳治疗策略。
Nat Med. 2018 Nov;24(11):1716-1720. doi: 10.1038/s41591-018-0213-5. Epub 2018 Oct 22.

Machine Learning in Clinical Journals: Moving From Inscrutable to Informative.

作者信息

Singh Karandeep, Beam Andrew L, Nallamothu Brahmajee K

机构信息

Department of Learning Health Sciences (K.S.), University of Michigan Medical School, Ann Arbor.

Department of Internal Medicine (K.S., B.K.N.), University of Michigan Medical School, Ann Arbor.

出版信息

Circ Cardiovasc Qual Outcomes. 2020 Oct;13(10):e007491. doi: 10.1161/CIRCOUTCOMES.120.007491. Epub 2020 Oct 14.

DOI:10.1161/CIRCOUTCOMES.120.007491
PMID:33079583
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9126253/
Abstract
摘要