Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data

@article{Huo2022DensityAwarePT,
  title={Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data},
  author={Zepeng Huo and Xiaoning Qian and Shuai Huang and Zhangyang Wang and Bobak J. Mortazavi},
  journal={ArXiv},
  year={2022},
  volume={abs/2207.11382}
}
Medical events of interest, such as mortality, often happen at a low rate in electronic medical records, as most admitted patients survive. Training models with this imbalance rate (class density discrepancy) may lead to suboptimal prediction. Traditionally this problem is addressed through ad-hoc methods such as resampling or reweighting but performance in many cases is still limited. We propose a framework for training models for this imbalance issue: 1) we first decouple the feature… 

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