AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration

@article{Ma2020AdaCareEC,
  title={AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration},
  author={Liantao Ma and Junyi Gao and Yasha Wang and Chaohe Zhang and Jiangtao Wang and Wenjie Ruan and Wen Tang and Xin Gao and Xinyu Ma},
  journal={ArXiv},
  year={2020},
  volume={abs/1911.12205}
}
Deep learning-based health status representation learning and clinical prediction have raised much research interest in recent years. Existing models have shown superior performance, but there are still several major issues that have not been fully taken into consideration. First, the historical variation pattern of the biomarker in diverse time scales plays a vital role in indicating the health status, but it has not been explicitly extracted by existing works. Second, key factors that… Expand
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