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

Runze LiYu TianZhuyi ShenJin LiJun LiKe-Feng DingJing-Song Li
Published in: JMIR medical informatics (2023)
Training clinical prediction models on label-deficient EHRs is indispensable in data-driven research. The proposed method has great potential to exploit the intrinsic structure of EHRs and achieve comparable learning performance to supervised methods.
Keyphrases
  • electronic health record
  • machine learning
  • clinical decision support
  • risk assessment
  • replacement therapy
  • climate change