Risk Stratification of ICU Patients Using Topic Models Inferred from Unstructured Progress Notes

@article{Lehman2012RiskSO,
  title={Risk Stratification of ICU Patients Using Topic Models Inferred from Unstructured Progress Notes},
  author={Li-wei H. Lehman and Mohammed Saeed and William J. Long and Joon Lee and Roger G. Mark},
  journal={AMIA ... Annual Symposium proceedings. AMIA Symposium},
  year={2012},
  volume={2012},
  pages={505-11}
}
We propose a novel approach for ICU patient risk stratification by combining the learned "topic" structure of clinical concepts (represented by UMLS codes) extracted from the unstructured nursing notes with physiologic data (from SAPS-I) for hospital mortality prediction. We used Hierarchical Dirichlet Processes (HDP), a non-parametric topic modeling technique, to automatically discover "topics" as shared groups of co-occurring UMLS clinical concepts. We evaluated the potential utility of the… CONTINUE READING
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