The "inconvenient truth" about AI in healthcare.
作者信息
Panch Trishan, Mattie Heather, Celi Leo Anthony
机构信息
1Division of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA USA.
Wellframe Inc., Boston, MA USA.
出版信息
NPJ Digit Med. 2019 Aug 16;2:77. doi: 10.1038/s41746-019-0155-4. eCollection 2019.
Abstract
摘要
相似文献
1
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.
2
Truth and opinion in climate change discourse: the Gore-Hansen disagreement.气候变化话语中的事实与观点：戈尔-汉森分歧。
Public Underst Sci. 2011 Nov;20(6):796-809. doi: 10.1177/0963662510364201.
3
Inconvenient truth or public health threat?不便说出的真相还是公共健康威胁？
S Afr Med J. 2013 Jan 17;103(2):69-71. doi: 10.7196/samj.6663.
4
Ground truth generalizability affects performance of the artificial intelligence model in automated vertebral fracture detection on plain lateral radiographs of the spine.真实情况的可推广性会影响人工智能模型在脊柱正位侧位X线片自动检测椎体骨折中的性能。
Spine J. 2022 Apr;22(4):511-523. doi: 10.1016/j.spinee.2021.10.020. Epub 2021 Nov 1.
5
Commercially-available AI algorithm improves radiologists' sensitivity for wrist and hand fracture detection on X-ray, compared to a CT-based ground truth.商业可用的人工智能算法提高了放射科医生在 X 光片上对手腕和手部骨折检测的敏感性，与基于 CT 的金标准相比。
Eur Radiol. 2024 May;34(5):2885-2894. doi: 10.1007/s00330-023-10380-1. Epub 2023 Nov 3.
6
[An inconvenient truth].[难以忽视的真相]
Tidsskr Nor Laegeforen. 2017 Sep 4;137(16). doi: 10.4045/tidsskr.17.0720. Print 2017 Sep 5.
7
Another inconvenient truth. In Europe, no one apparently wants to listen if you have good news about genetically modified organisms (GMOs).另一个难以忽视的真相。在欧洲，如果您有关于转基因生物（GMO）的好消息，显然没人愿意听。
Nat Biotechnol. 2007 Dec;25(12):1330. doi: 10.1038/nbt1207-1330.
8
Disparity in rehabilitation: another inconvenient truth.康复领域的差距：另一个难以忽视的真相。
Arch Phys Med Rehabil. 2015 Aug;96(8):1371-4. doi: 10.1016/j.apmr.2015.04.017. Epub 2015 May 7.
9
Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis.公众对人工智能在医疗保健中应用的看法：定性元分析。
BMJ Open. 2023 Jan 4;13(1):e066322. doi: 10.1136/bmjopen-2022-066322.
10
Widespread use of performance-enhancing drugs-an inconvenient truth.提高成绩药物的广泛使用——一个难以忽视的真相。
Endocr Rev. 2014 Dec;35(6):E1-2. doi: 10.1210/er.2014-1047.
引用本文的文献
1
Advancing standards in biomedical image analysis validation: A perspective on Metrics Reloaded.生物医学图像分析验证标准的进展：对“指标再审视”的一种观点
Clin Transl Med. 2025 Sep;15(9):e70237. doi: 10.1002/ctm2.70237.
2
Gated recurrent unit with decay has real-time capability for postoperative ileus surveillance and offers cross-hospital transferability.具有衰减功能的门控循环单元具有术后肠梗阻监测的实时能力，并具备跨医院的可转移性。
Commun Med (Lond). 2025 Aug 4;5(1):331. doi: 10.1038/s43856-025-01053-9.
3
Contrasting attitudes towards current and future artificial intelligence applications for computerised interpretation of electrocardiograms: a clinical stakeholder interview study.对当前及未来用于心电图计算机解读的人工智能应用的不同态度：一项临床利益相关者访谈研究
JAMIA Open. 2025 Jul 21;8(4):ooaf071. doi: 10.1093/jamiaopen/ooaf071. eCollection 2025 Aug.
4
Assessing Clinicians' Legal Concerns and the Need for a Regulatory Framework for AI in Healthcare: A Mixed-Methods Study.评估临床医生的法律担忧以及医疗保健领域人工智能监管框架的必要性：一项混合方法研究。
Healthcare (Basel). 2025 Jun 21;13(13):1487. doi: 10.3390/healthcare13131487.
5
Privacy, ethics, transparency, and accountability in AI systems for wearable devices.可穿戴设备人工智能系统中的隐私、伦理、透明度与问责制。
Front Digit Health. 2025 Jun 17;7:1431246. doi: 10.3389/fdgth.2025.1431246. eCollection 2025.
6
The Digital Transformation of Healthcare Through Intelligent Technologies: A Path Dependence-Augmented-Unified Theory of Acceptance and Use of Technology Model for Clinical Decision Support Systems.通过智能技术实现医疗保健的数字化转型：临床决策支持系统的技术接受与使用的路径依赖增强统一理论模型
Healthcare (Basel). 2025 May 22;13(11):1222. doi: 10.3390/healthcare13111222.
7
Proactive vs. passive algorithmic ethics practices in healthcare: the moderating role of healthcare engagement type in patients' responses.医疗保健中主动与被动算法伦理实践：医疗保健参与类型在患者反应中的调节作用。
BMC Med Ethics. 2025 Jun 7;26(1):73. doi: 10.1186/s12910-025-01236-y.
8
AI in Neurology: Everything, Everywhere, all at Once PART 2: Speech, Sentience, Scruples, and Service.神经病学中的人工智能：瞬息全宇宙 第二部分：言语、感知、顾虑与服务
Ann Neurol. 2025 Sep;98(3):431-447. doi: 10.1002/ana.27229. Epub 2025 May 27.
9
Chinese generative AI models (DeepSeek and Qwen) rival ChatGPT-4 in ophthalmology queries with excellent performance in Arabic and English.中国生成式人工智能模型（通义千问和文心一言）在眼科问题查询方面可与ChatGPT-4相媲美，在阿拉伯语和英语方面表现出色。
Narra J. 2025 Apr;5(1):e2371. doi: 10.52225/narra.v5i1.2371. Epub 2025 Apr 8.
10
Generative AI Decision-Making Attributes in Complex Health Services: A Rapid Review.复杂医疗服务中的生成式人工智能决策属性：快速综述
Cureus. 2025 Jan 30;17(1):e78257. doi: 10.7759/cureus.78257. eCollection 2025 Jan.
本文引用的文献
1
Artificial intelligence: opportunities and risks for public health.人工智能：公共卫生的机遇与风险。
Lancet Digit Health. 2019 May;1(1):e13-e14. doi: 10.1016/S2589-7500(19)30002-0. Epub 2019 May 2.
2
Health intelligence: how artificial intelligence transforms population and personalized health.健康智能：人工智能如何改变群体与个性化健康。
NPJ Digit Med. 2018 Oct 2;1:53. doi: 10.1038/s41746-018-0058-9. eCollection 2018.
3
With an eye to AI and autonomous diagnosis.着眼于人工智能与自主诊断。
NPJ Digit Med. 2018 Aug 28;1:40. doi: 10.1038/s41746-018-0048-y. eCollection 2018.
4
Scalable and accurate deep learning with electronic health records.借助电子健康记录实现可扩展且准确的深度学习。
NPJ Digit Med. 2018 May 8;1:18. doi: 10.1038/s41746-018-0029-1. eCollection 2018.
5
Artificial intelligence powers digital medicine.人工智能推动数字医学发展。
NPJ Digit Med. 2018 Mar 14;1:5. doi: 10.1038/s41746-017-0012-2. eCollection 2018.
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
Machine Learning in Medicine.医学中的机器学习
N Engl J Med. 2019 Apr 4;380(14):1347-1358. doi: 10.1056/NEJMra1814259.
8
Artificial intelligence, machine learning and health systems.人工智能、机器学习与卫生系统。
J Glob Health. 2018 Dec;8(2):020303. doi: 10.7189/jogh.08.020303.
9
A systematic review of the clinical application of data-driven population segmentation analysis.数据驱动的人群细分分析在临床应用中的系统评价。
BMC Med Res Methodol. 2018 Nov 3;18(1):121. doi: 10.1186/s12874-018-0584-9.
10
Systematic Review of Validity Assessments of Framingham Risk Score Results in Health Economic Modelling of Lipid-Modifying Therapies in Europe.欧洲降脂治疗药物健康经济学模型中弗雷明汉风险评分结果的有效性评估系统综述。
Pharmacoeconomics. 2018 Feb;36(2):205-213. doi: 10.1007/s40273-017-0578-1.
Zotero 插件