This paper is in the following e-collection/theme issue:

Design and Usability of Clinical Software and EHRs (271) Machine Learning (1501) Clinical Information and Decision Making (1434) Security and Privacy of mHealth and uHealth (126) Tools, Programs and Algorithms (275) Ethics, Privacy, and Legal Issues (494) eHealth Infrastructures (357) Focus Groups and Qualitative Research for Human Factors Research (880) Secondary Use of Clinical Data for Research and Surveillance (375) Big Data (245)

Published on in Vol 8, No 3 (2021): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21810, first published .
Machine Learning–Based Analysis of Encrypted Medical Data in the Cloud: Qualitative Study of Expert Stakeholders’ Perspectives

Machine Learning–Based Analysis of Encrypted Medical Data in the Cloud: Qualitative Study of Expert Stakeholders’ Perspectives

Machine Learning–Based Analysis of Encrypted Medical Data in the Cloud: Qualitative Study of Expert Stakeholders’ Perspectives

Authors of this article:

Ala Sarah Alaqra1 Author Orcid Image ;   Bridget Kane2 Author Orcid Image ;   Simone Fischer-Hübner3 Author Orcid Image
Article Authors Cited by (14) Tweetations (2) Metrics

Journals

  1. Cumyn A, Ménard J, Barton A, Dault R, Lévesque F, Ethier J. Patients’ and Members of the Public’s Wishes Regarding Transparency in the Context of Secondary Use of Health Data: Scoping Review. Journal of Medical Internet Research 2023;25:e45002 View
  2. Park M, Moon K. Web-Based Delirium Prevention Application for Long-Term Care Facilities. Journal of the American Medical Directors Association 2023;24(4):559 View
  3. Banerjee D, Adhikary S, Bhattacharya S, Chakraborty A, Dutta S, Chatterjee S, Ganguly A, Nanda S, Rajak P. Breaking boundaries: Artificial intelligence for pesticide detection and eco-friendly degradation. Environmental Research 2024;241:117601 View
  4. Shevtsova D, Ahmed A, Boot I, Sanges C, Hudecek M, Jacobs J, Hort S, Vrijhoef H. Trust in and Acceptance of Artificial Intelligence Applications in Medicine: Mixed Methods Study. JMIR Human Factors 2024;11:e47031 View
  5. Tino C, Becker A, Pereira B, Corrêa L, Soares M, Nascimento-e-Silva D. Ethical, legal, and information management aspects in the context of patient safety. Revista de Gestão e Secretariado 2024;15(1):167 View
  6. Partyka A, Mykhaylova O, Shpak S. DETECTION, ANALYSIS AND PROTECTION OF CONFIDENTIAL DATA USING AMAZON MACIE MACHINE LEARNING TECHNOLOGY. Cybersecurity: Education, Science, Technique 2024;3(23):132 View
  7. Tazi F, Nandakumar A, Dykstra J, Rajivan P, Das S. SoK: Analyzing Privacy and Security of Healthcare Data from the User Perspective. ACM Transactions on Computing for Healthcare 2024;5(2):1 View
  8. Iwaya L, Alaqra A, Hansen M, Fischer-Hübner S. Privacy impact assessments in the wild: A scoping review. Array 2024;23:100356 View
  9. Mooghali M, Stroud A, Yoo D, Barry B, Grimshaw A, Ross J, Zhu X, Miller J. Trustworthy and ethical AI-enabled cardiovascular care: a rapid review. BMC Medical Informatics and Decision Making 2024;24(1) View
  10. Bhanbhro J, Nisticò S, Palopoli L. Issues in federated learning: some experiments and preliminary results. Scientific Reports 2024;14(1) View

Books/Policy Documents

  1. Alaqra A, Fischer-Hübner S, Karegar F. HCI for Cybersecurity, Privacy and Trust. View
  2. Fischer-Hübner S, Karegar F. The Curious Case of Usable Privacy. View
  3. Fischer-Hübner S, Karegar F. The Curious Case of Usable Privacy. View
  4. Fischer-Hübner S, Karegar F. The Curious Case of Usable Privacy. View