Knowledge Graph Embeddings for ICU readmission prediction.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: Intensive Care Unit (ICU) readmissions represent both a health risk for patients,with increased mortality rates and overall health deterioration, and a financial burden for healthcare facilities. As healthcare became more data-driven with the introduction of Electronic Health Records (EHR), machine learning methods have been applied to predict ICU readmission risk. However, these methods disregard the meaning and relationships of data objects and work blindly over clinical data without taking into account scientific knowledge and context. Ontologies and Knowledge Graphs can help bridge this gap between data and scientific context, as they are computational artefacts that represent the entities of a domain and their relationships to each other in a formalized way.

Authors

  • Ricardo M S Carvalho
    LASIGE, Faculty of Sciences, University of Lisbon, Lisbon, Portugal. rmscarvalho@fc.ul.pt.
  • Daniela Oliveira
    Insight Centre for Data Analytics, NUI Galway, Galway Business Park, Dangan, Galway, H91 AEX4, Ireland. daniela.oliveira@insight-centre.org.
  • Catia Pesquita
    Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa, Portugal.