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

Machine Learning (2033) Theme Issue 2021: Emerging Challenges and Advancements In Health Informatics with New Generation Unsupervised Learning (1) Advanced Data Analytics in eHealth (203)

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
Article Authors Cited by (4) Tweetations (2) Metrics

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