Corpus ID: 231846970

Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration

@inproceedings{Aken2021ClinicalOP,
  title={Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration},
  author={Betty van Aken and Jens-Michalis Papaioannou and M. Mayrdorfer and K. Budde and F. Gers and Alexander Loser},
  booktitle={EACL},
  year={2021}
}
Outcome prediction from clinical text can prevent doctors from overlooking possible risks and help hospitals to plan capacities. We simulate patients at admission time, when decision support can be especially valuable, and contribute a novel *admission to discharge* task with four common outcome prediction targets: Diagnoses at discharge, procedures performed, in-hospital mortality and length-of-stay prediction. The ideal system should infer outcomes based on symptoms, pre-conditions and risk… Expand
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References

SHOWING 1-10 OF 47 REFERENCES
Towards unstructured mortality prediction with free-text clinical notes
Viewpoint Paper: Identifying Patient Smoking Status from Medical Discharge Records
An Analysis of Attention over Clinical Notes for Predictive Tasks
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare
Ontological attention ensembles for capturing semantic concepts in ICD code prediction from clinical text
...
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3
4
5
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