Learning Electronic Health Records through HyperbolicEmbedding of Medical Ontologies

Date and time: 
Friday, March 13, 2020 - 08:30
200 Deschutes
Qiuhao Lu
University of Oregon
  • Dejing Dou (Chair)
  • Thanh Nguyen
  • Thien Nguyen

Unplanned intensive care units (ICU) readmissions and in-hospital mortality of patients are two important metrics for evaluating the quality of hospital care. Identifying patients with higher risk of readmission to ICU or of mortality can not only protect those patients from potential dangers, but also reduce the high costs of healthcare. In this work, we propose a new method to incorporate information from the Electronic Health Records (EHRs) of patients and utilize hyperbolic embeddings of a medical ontology (i.e., ICD-9) in the prediction model. The results prove the effectiveness of our method and show that hyperbolic embeddings of ontological concepts give promising performance.