Capturing Feature-Level Irregularity in Disease Progression Modeling

@inproceedings{Zheng2017CapturingFI,
  title={Capturing Feature-Level Irregularity in Disease Progression Modeling},
  author={Kaiping Zheng and Wei Wang and Jinyang Gao and Kee Yuan Ngiam and Beng Chin Ooi and James Wei Luen Yip},
  booktitle={CIKM},
  year={2017}
}
Disease progression modeling (DPM) analyzes patients' electronic medical records (EMR) to predict the health state of patients, which facilitates accurate prognosis, early detection and treatment of chronic diseases. However, EMR are irregular because patients visit hospital irregularly based on the need of treatment. For each visit, they are typically given different diagnoses, prescribed various medications and lab tests. Consequently, EMR exhibit irregularity at the feature level. To handle… CONTINUE READING

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RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

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In Advances in Neural Information Processing Systems • 2016
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