Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.
作者信息
Obermeyer Ziad, Emanuel Ezekiel J
机构信息
From the Department of Emergency Medicine, Harvard Medical School and Brigham and Women's Hospital, and the Department of Health Care Policy, Harvard Medical School, Boston (Z.O.); and the Department of Medical Ethics and Health Policy, Perelman School of Medicine, and the Department of Health Care Management, Wharton School, University of Pennsylvania, Philadelphia (E.J.E.).
出版信息
N Engl J Med. 2016 Sep 29;375(13):1216-9. doi: 10.1056/NEJMp1606181.
Abstract
摘要
相似文献
1
Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.预测未来——大数据、机器学习与临床医学。
N Engl J Med. 2016 Sep 29;375(13):1216-9. doi: 10.1056/NEJMp1606181.
2
Machine Learning and Network Methods for Biology and Medicine.生物学与医学中的机器学习和网络方法
Comput Math Methods Med. 2015;2015:915124. doi: 10.1155/2015/915124. Epub 2015 Nov 29.
3
Unintended Consequences of Machine Learning in Medicine.机器学习在医学领域的意外后果。
JAMA. 2017 Aug 8;318(6):517-518. doi: 10.1001/jama.2017.7797.
4
Introducing Machine Learning Concepts with WEKA.使用WEKA介绍机器学习概念。
Methods Mol Biol. 2016;1418:353-78. doi: 10.1007/978-1-4939-3578-9_17.
5
Causality in digital medicine.数字医学中的因果关系。
Nat Commun. 2021 Sep 15;12(1):5471. doi: 10.1038/s41467-021-25743-9.
6
Ascent of machine learning in medicine.机器学习在医学领域的兴起。
Nat Mater. 2019 May;18(5):407. doi: 10.1038/s41563-019-0360-1.
7
Can Computers Be Made to Respect the Art of Medicine?计算机能否学会尊重医学艺术？
South Med J. 2017 Jun;110(6):425. doi: 10.14423/SMJ.0000000000000656.
8
Predictive Analytics through Machine Learning in the clinical settings.临床环境中通过机器学习进行预测分析。
Comput Methods Programs Biomed. 2017 Jun;144:A1-A2. doi: 10.1016/S0169-2607(17)30552-7.
9
Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.基于机器学习的微卫星变异分类：一种用于橄榄种群系统地理学特征描述的有效方法。
PLoS One. 2015 Nov 24;10(11):e0143465. doi: 10.1371/journal.pone.0143465. eCollection 2015.
10
A Cloud-Based Infrastructure for Feedback-Driven Training and Image Recognition.一种用于反馈驱动训练和图像识别的基于云的基础设施。
Stud Health Technol Inform. 2015;216:691-5.
引用本文的文献
1
Predicting the risk of threatened abortion using machine learning methods: a comparative study.使用机器学习方法预测先兆流产风险：一项比较研究。
BMC Pregnancy Childbirth. 2025 Aug 30;25(1):901. doi: 10.1186/s12884-025-08030-z.
2
International Partnerships in AI-Driven Healthcare: Opportunities and Challenges for Advancing the UN Sustainable Development Goals-A Perspective.人工智能驱动的医疗保健领域的国际伙伴关系：推动联合国可持续发展目标的机遇与挑战——一种视角
Healthcare (Basel). 2025 Aug 20;13(16):2053. doi: 10.3390/healthcare13162053.
3
Development of a Serum Proteomic-Based Diagnostic Model for Lung Cancer Using Machine Learning Algorithms and Unveiling the Role of SLC16A4 in Tumor Progression and Immune Response.利用机器学习算法开发基于血清蛋白质组学的肺癌诊断模型并揭示SLC16A4在肿瘤进展和免疫反应中的作用
Biomolecules. 2025 Jul 26;15(8):1081. doi: 10.3390/biom15081081.
4
Machine Learning for Predicting Thromboembolic Events Following Flow Diverter Treatment of Intracranial Aneurysms: A Multicenter Retrospective Study.机器学习用于预测颅内动脉瘤血流导向治疗后的血栓栓塞事件：一项多中心回顾性研究
Neurol Ther. 2025 Aug 27. doi: 10.1007/s40120-025-00808-9.
5
Guidelines From the American Society of Pain and Neuroscience for Using Artificial Intelligence in Interventional Spine and Nerve Treatment.美国疼痛与神经科学学会关于在介入性脊柱和神经治疗中使用人工智能的指南。
J Pain Res. 2025 Aug 20;18:4211-4235. doi: 10.2147/JPR.S529465. eCollection 2025.
6
Development and Validation of an Artificial Intelligence-Driven Model for Accurate Classification of Erythrodermic Psoriasis Severity: Erythrodermic Psoriasis Integrated Classification System (EPICS).人工智能驱动的红皮病型银屑病严重程度准确分类模型的开发与验证：红皮病型银屑病综合分类系统（EPICS）
Am J Clin Dermatol. 2025 Aug 26. doi: 10.1007/s40257-025-00980-6.
7
Fibroblast activation protein expression in the tumor microenvironment is crucial in survival prediction and differentiation of recurrent gliomas: a head-to-head comparison of Ga-FAPI-04 and F-FET in PET/CT imaging.肿瘤微环境中纤维母细胞活化蛋白的表达在复发性胶质瘤的生存预测和分化中至关重要：PET/CT成像中Ga-FAPI-04与F-FET的直接比较
EJNMMI Radiopharm Chem. 2025 Aug 26;10(1):57. doi: 10.1186/s41181-025-00378-z.
8
Diagnostic Prediction Models for Primary Care, Based on AI and Electronic Health Records: Systematic Review.基于人工智能和电子健康记录的基层医疗诊断预测模型：系统评价
JMIR Med Inform. 2025 Aug 22;13:e62862. doi: 10.2196/62862.
9
How New Chatbots Can Support Personalized Medicine.新型聊天机器人如何助力个性化医疗。
Healthc Inform Res. 2025 Jul;31(3):245-252. doi: 10.4258/hir.2025.31.3.245. Epub 2025 Jul 31.
10
A machine learning approach to predict self-efficacy in breast cancer survivors.一种预测乳腺癌幸存者自我效能的机器学习方法。
BMC Med Inform Decis Mak. 2025 Aug 19;25(1):313. doi: 10.1186/s12911-025-03155-9.
本文引用的文献
1
Prediction Policy Problems.预测政策问题。
Am Econ Rev. 2015 May;105(5):491-495. doi: 10.1257/aer.p20151023.
2
Restoring cortical control of functional movement in a human with quadriplegia.恢复四肢瘫痪患者的功能性运动的皮质控制。
Nature. 2016 May 12;533(7602):247-50. doi: 10.1038/nature17435. Epub 2016 Apr 13.
3
Single reading with computer-aided detection for screening mammography.在乳腺钼靶筛查中采用计算机辅助检测进行单次读片。
N Engl J Med. 2008 Oct 16;359(16):1675-84. doi: 10.1056/NEJMoa0803545. Epub 2008 Oct 1.
Zotero 插件