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

Security in Digital Health (49) Artificial Intelligence (2060) Electronic Health Records (1295) Machine Learning (2032)

Published on in Vol 10, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38440, first published .
Exploiting Missing Value Patterns for a Backdoor Attack on Machine Learning Models of Electronic Health Records: Development and Validation Study

Exploiting Missing Value Patterns for a Backdoor Attack on Machine Learning Models of Electronic Health Records: Development and Validation Study

Exploiting Missing Value Patterns for a Backdoor Attack on Machine Learning Models of Electronic Health Records: Development and Validation Study

Authors of this article:

Byunggill Joe1 Author Orcid Image ;   Yonghyeon Park2 Author Orcid Image ;   Jihun Hamm3 Author Orcid Image ;   Insik Shin1 Author Orcid Image ;   Jiyeon Lee4 Author Orcid Image
Article Authors Cited by (4) Tweetations (2) Metrics

Journals

  1. Mengara O, Avila A, Falk T. Backdoor Attacks to Deep Neural Networks: A Survey of the Literature, Challenges, and Future Research Directions. IEEE Access 2024;12:29004 View
  2. Bryan J, Li D. Comments on Contemporary Uses of Machine Learning for Electronic Health Records. North Carolina Medical Journal 2024;85(4) View
  3. Kühlem R, Otten D, Ludwig D, Hudde A, Rosenbaum A, Mauthe A. Backdoor Attacks on DNN and GBDT: A Case Study From the Insurance Domain. Applied Stochastic Models in Business and Industry 2025;41(5) View

Books/Policy Documents

  1. Robinette P, Nguyen T, Sasaki S, Johnson T. Computer Security – ESORICS 2025. View