Published on in Vol 10, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34724, first published .
Noninvasive Screening Tool for Hyperkalemia Using a Single-Lead Electrocardiogram and Deep Learning: Development and Usability Study

Noninvasive Screening Tool for Hyperkalemia Using a Single-Lead Electrocardiogram and Deep Learning: Development and Usability Study

Noninvasive Screening Tool for Hyperkalemia Using a Single-Lead Electrocardiogram and Deep Learning: Development and Usability Study

Journals

  1. Gu K, Liu J, Shi S, Xie S, Shi T, Qiao J. Self-Organizing Multichannel Deep Learning System for River Turbidity Monitoring. IEEE Transactions on Instrumentation and Measurement 2022;71:1 View
  2. Stauss M, Htay H, Kooman J, Lindsay T, Woywodt A. Wearables in Nephrology: Fanciful Gadgetry or Prêt-à-Porter?. Sensors 2023;23(3):1361 View
  3. Regolisti G, Rossi G, Genovesi S. Can we trust ECG for diagnosing hyperkalemia? A challenging question for clinicians and bioengineers. International Journal of Cardiology 2023;393:131380 View
  4. Holmstrom L, Christensen M, Yuan N, Weston Hughes J, Theurer J, Jujjavarapu M, Fatehi P, Kwan A, Sandhu R, Ebinger J, Cheng S, Zou J, Chugh S, Ouyang D. Deep learning-based electrocardiographic screening for chronic kidney disease. Communications Medicine 2023;3(1) View
  5. An J, Park M, Joo S, Chang M, Kim D, Shin D, Na Y, Kim J, Lee H, Song Y, Lee Y, Kim S. Development of deep learning algorithm for detecting dyskalemia based on electrocardiogram. Scientific Reports 2024;14(1) View