• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

Data Science: Big Data, Machine Learning, and Artificial Intelligence.

作者信息

Carlos Ruth C, Kahn Charles E, Halabi Safwan

机构信息

Department of Radiology, University of Michigan, Ann Arbor, Michigan.

Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.

出版信息

J Am Coll Radiol. 2018 Mar;15(3 Pt B):497-498. doi: 10.1016/j.jacr.2018.01.029.

DOI:10.1016/j.jacr.2018.01.029
PMID:29502583
Abstract
摘要

相似文献

1
Data Science: Big Data, Machine Learning, and Artificial Intelligence.数据科学：大数据、机器学习与人工智能。
J Am Coll Radiol. 2018 Mar;15(3 Pt B):497-498. doi: 10.1016/j.jacr.2018.01.029.
2
Data science, artificial intelligence, and machine learning: Opportunities for laboratory medicine and the value of positive regulation.数据科学、人工智能与机器学习：检验医学的机遇及积极监管的价值
Clin Biochem. 2019 Jul;69:1-7. doi: 10.1016/j.clinbiochem.2019.04.013. Epub 2019 Apr 22.
3
Big Data, Big Impact: The Potential for Data Science in Neurosurgery.大数据，重大影响：神经外科领域数据科学的潜力
World Neurosurg. 2020 Jun;138:558-559. doi: 10.1016/j.wneu.2020.03.182.
4
Big Data and Complex Data Analytics: Breaking Peer Review?大数据与复杂数据分析：会打破同行评议吗？
J Dent Res. 2022 Apr;101(4):369-370. doi: 10.1177/00220345211070983. Epub 2022 Jan 20.
5
Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology.大数据和机器学习在放射诊断决策支持中的作用。
J Am Coll Radiol. 2018 Mar;15(3 Pt B):569-576. doi: 10.1016/j.jacr.2018.01.028.
6
Artificial Intelligence and Big Data Science in Neurocritical Care.人工智能与神经危重症大数据科学
Crit Care Clin. 2023 Jan;39(1):235-242. doi: 10.1016/j.ccc.2022.07.008. Epub 2022 Oct 9.
7
Big Data and Radiology Research.大数据与放射学研究。
J Am Coll Radiol. 2019 Sep;16(9 Pt B):1347-1350. doi: 10.1016/j.jacr.2019.06.003.
8
m-Health 2.0: New perspectives on mobile health, machine learning and big data analytics.移动医疗 2.0：移动医疗、机器学习和大数据分析的新视角。
Methods. 2018 Dec 1;151:34-40. doi: 10.1016/j.ymeth.2018.05.015. Epub 2018 Jun 8.
9
Interpretable Artificial Intelligence: Why and When.可解释人工智能：为何与何时。
AJR Am J Roentgenol. 2020 May;214(5):1137-1138. doi: 10.2214/AJR.19.22145. Epub 2020 Mar 4.
10
Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.人工智能和机器学习在放射学中的应用：机遇、挑战、陷阱和成功标准。
J Am Coll Radiol. 2018 Mar;15(3 Pt B):504-508. doi: 10.1016/j.jacr.2017.12.026. Epub 2018 Feb 4.

引用本文的文献

1
Machine learning for the prediction of augmented renal clearance (ARC) in patients with sepsis in critical care units.用于预测重症监护病房脓毒症患者肾脏清除率增加（ARC）的机器学习
Sci Rep. 2025 Jul 18;15(1):26119. doi: 10.1038/s41598-025-11313-2.
2
Predicting Factors Affecting Survival Rate in Patients Undergoing On-Pump Coronary Artery Bypass Graft Surgery Using Machine Learning Methods: A Systematic Review.使用机器学习方法预测接受体外循环冠状动脉旁路移植术患者生存率的影响因素：一项系统评价
Health Sci Rep. 2025 Jan 22;8(1):e70336. doi: 10.1002/hsr2.70336. eCollection 2025 Jan.
3
Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study.
医学生和病理学实习生对人工智能的认知与态度：调查研究
JMIR Med Educ. 2025 Jan 10;11:e62669. doi: 10.2196/62669.
4
Presurgical Upgrade Prediction of DCIS to Invasive Ductal Carcinoma Using Time-dependent Deep Learning Models with DCE MRI.使用基于 DCE MRI 的时变深度学习模型对 DCIS 进行术前升级预测为浸润性导管癌。
Radiol Artif Intell. 2024 Sep;6(5):e230348. doi: 10.1148/ryai.230348.
5
Artificial intelligence in radiology: Are Saudi residents ready, prepared, and knowledgeable?人工智能在放射学中的应用：沙特居民是否已做好准备并具备相关知识？
Saudi Med J. 2022 Jan;43(1):53-60. doi: 10.15537/smj.2022.43.1.20210337.
6
Artificial Intelligence in Medicine: A Multinational Multi-Center Survey on the Medical and Dental Students' Perception.人工智能在医学中的应用：对医学生和牙科学学生感知的一项多国多中心调查。
Front Public Health. 2021 Dec 24;9:795284. doi: 10.3389/fpubh.2021.795284. eCollection 2021.
7
Structured Reporting of Computed Tomography and Magnetic Resonance in the Staging of Pancreatic Adenocarcinoma: A Delphi Consensus Proposal.胰腺癌分期中计算机断层扫描和磁共振成像的结构化报告：德尔菲共识提案
Diagnostics (Basel). 2021 Nov 3;11(11):2033. doi: 10.3390/diagnostics11112033.
8
Structured Reporting of Lung Cancer Staging: A Consensus Proposal.肺癌分期的结构化报告：一项共识提案。
Diagnostics (Basel). 2021 Aug 30;11(9):1569. doi: 10.3390/diagnostics11091569.
9
Comparative analysis of machine learning algorithms for computer-assisted reporting based on fully automated cross-lingual RadLex mappings.基于全自动跨语言 RadLex 映射的计算机辅助报告机器学习算法的比较分析。
Sci Rep. 2021 Mar 9;11(1):5529. doi: 10.1038/s41598-021-85016-9.
10
Artificial Intelligence in Modern Medicine - The Evolving Necessity of the Present and Role in Transforming the Future of Medical Care.现代医学中的人工智能——当下不断发展的必要性及其在改变医疗未来中的作用。
Cureus. 2020 May 9;12(5):e8041. doi: 10.7759/cureus.8041.