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本文引用的文献

1
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.基于监督机器学习技术开发的预测模型研究中的偏倚风险：系统评价。
BMJ. 2021 Oct 20;375:n2281. doi: 10.1136/bmj.n2281.
2
Evaluation of artificial intelligence on a reference standard based on subjective interpretation.基于主观解读的参考标准对人工智能的评估。
Lancet Digit Health. 2021 Nov;3(11):e693-e695. doi: 10.1016/S2589-7500(21)00216-8. Epub 2021 Sep 21.
3
Equity in essence: a call for operationalising fairness in machine learning for healthcare.公平的本质：呼吁在医疗保健机器学习中实现公平性操作化。
BMJ Health Care Inform. 2021 Apr;28(1). doi: 10.1136/bmjhci-2020-100289.
4
How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices.机器学习如何嵌入以支持临床医生决策：对 FDA 批准的医疗设备的分析。
BMJ Health Care Inform. 2021 Apr;28(1). doi: 10.1136/bmjhci-2020-100301.
5
Health data poverty: an assailable barrier to equitable digital health care.健康数据贫困：公平数字医疗的可攻破障碍。
Lancet Digit Health. 2021 Apr;3(4):e260-e265. doi: 10.1016/S2589-7500(20)30317-4. Epub 2021 Mar 4.
6
Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.美国和欧洲对人工智能和基于机器学习的医疗器械的审批（2015-20）：比较分析。
Lancet Digit Health. 2021 Mar;3(3):e195-e203. doi: 10.1016/S2589-7500(20)30292-2. Epub 2021 Jan 18.
7
Time to reality check the promises of machine learning-powered precision medicine.是时候对机器学习驱动的精准医学的承诺进行现实检验了。
Lancet Digit Health. 2020 Dec;2(12):e677-e680. doi: 10.1016/S2589-7500(20)30200-4. Epub 2020 Sep 16.
8
The "inconvenient truth" about AI in healthcare.关于医疗保健领域人工智能的“难以忽视的真相”。
NPJ Digit Med. 2019 Aug 16;2:77. doi: 10.1038/s41746-019-0155-4. eCollection 2019.

An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research.

作者信息

Zhang Joe, Whebell Stephen, Gallifant Jack, Budhdeo Sanjay, Mattie Heather, Lertvittayakumjorn Piyawat, Del Pilar Arias Lopez Maria, Tiangco Beatrice J, Gichoya Judy W, Ashrafian Hutan, Celi Leo A, Teo James T

机构信息

Institute of Global Health Innovation, Imperial College London, London, UK; Department of Critical Care, King's College Hospital NHS Foundation Trust, London, UK.

Department of Critical Care, Townsville University Hospital, Queensland Health, Townsville, QLD, Australia.

出版信息

Lancet Digit Health. 2022 Apr;4(4):e212-e213. doi: 10.1016/S2589-7500(22)00032-2.

DOI:10.1016/S2589-7500(22)00032-2
PMID:35337638
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9150439/
Abstract
摘要