Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47862, first published .
Improving an Electronic Health Record–Based Clinical Prediction Model Under Label Deficiency: Network-Based Generative Adversarial Semisupervised Approach

Improving an Electronic Health Record–Based Clinical Prediction Model Under Label Deficiency: Network-Based Generative Adversarial Semisupervised Approach

Improving an Electronic Health Record–Based Clinical Prediction Model Under Label Deficiency: Network-Based Generative Adversarial Semisupervised Approach

Authors of this article:

Runze Li1 Author Orcid Image ;   Yu Tian1 Author Orcid Image ;   Zhuyi Shen1 Author Orcid Image ;   Jin Li2 Author Orcid Image ;   Jun Li3 Author Orcid Image ;   Kefeng Ding3 Author Orcid Image ;   Jingsong Li1 Author Orcid Image

Journals

  1. Ghebrehiwet I, Zaki N, Damseh R, Mohamad M. Revolutionizing personalized medicine with generative AI: a systematic review. Artificial Intelligence Review 2024;57(5) View
  2. Mishra A, Majumder A, Kommineni D, Anna Joseph C, Chowdhury T, Anumula S. Role of Generative Artificial Intelligence in Personalized Medicine: A Systematic Review. Cureus 2025 View
  3. Loni M, Poursalim F, Asadi M, Gharehbaghi A. A review on generative AI models for synthetic medical text, time series, and longitudinal data. npj Digital Medicine 2025;8(1) View

Conference Proceedings

  1. Liu J, Li Y, Jin Z, Ye J, Jiang J. 2023 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML). Deep learning-based particle gradation detection of fillers View