Protecting Your Patients' Interests in the Era of Big Data, Artificial Intelligence, and Predictive Analytics

被引:72
作者
Balthazar, Patricia [1 ]
Harri, Peter [1 ]
Prater, Adam [1 ]
Safdar, Nabile M. [1 ]
机构
[1] Emory Univ, Sch Med, Dept Radiol & Imaging Sci, 1364 Clifton Rd NE,Room D125A, Atlanta, GA 30322 USA
关键词
Artificial intelligence; machine learning; ethics; big data; informatics; INFORMED-CONSENT; DATA SCIENCE; PERSPECTIVES; ETHICS; HEALTH; QUESTIONS; ISSUES;
D O I
10.1016/j.jacr.2017.11.035
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
The Hippocratic oath and the Belmont report articulate foundational principles for how physicians interact with patients and research subjects. The increasing use of big data and artificial intelligence techniques demands a re-examination of these principles in light of the potential issues surrounding privacy, confidentiality, data ownership, informed consent, epistemology, and inequities. Patients have strong opinions about these issues. Radiologists have a fiduciary responsibility to protect the interest of their patients. As such, the community of radiology leaders, ethicists, and informaticists must have a conversation about the appropriate way to deal with these issues and help lead the way in developing capabilities in the most just, ethical manner possible.
引用
收藏
页码:580 / 586
页数:7
相关论文
共 56 条
  • [1] American Health Information Management Association, AHIMA COD ETH
  • [2] Andrejevic M., 2014, Int. J. Commun., V8, P1673
  • [3] [Anonymous], 1995, Artificial Intelligence
  • [4] [Anonymous], 2012, Nw. J. Tech. Intell. Prop
  • [5] [Anonymous], 2012, Philosophy Technology, DOI [10.1007/s13347-012-0093-4, DOI 10.1007/S13347-012-0093-4]
  • [6] Berry DM, COMPUTATIONAL TURN T
  • [7] Bhattasali N, MACH LEARN 2015
  • [8] Blumenthal R, YOURE NOT ANGRY EQUI
  • [9] CRITICAL QUESTIONS FOR BIG DATA Provocations for a cultural, technological, and scholarly phenomenon
    Boyd, Danah
    Crawford, Kate
    [J]. INFORMATION COMMUNICATION & SOCIETY, 2012, 15 (05) : 662 - 679
  • [10] Semantics derived automatically from language corpora contain human-like biases
    Caliskan, Aylin
    Bryson, Joanna J.
    Narayanan, Arvind
    [J]. SCIENCE, 2017, 356 (6334) : 183 - 186