ROAD2H: Development and evaluation of an open-source explainable artificial intelligence approach for managing co-morbidity and clinical guidelines.

Journal: Learning health systems
Published Date: Sep 12, 2023

Abstract

INTRODUCTION: Clinical decision support (CDS) systems (CDSSs) that integrate clinical guidelines need to reflect real-world co-morbidity. In patient-specific clinical contexts, transparent recommendations that allow for contraindications and other conflicts arising from co-morbidity are a requirement. In this work, we develop and evaluate a non-proprietary, standards-based approach to the deployment of computable guidelines with explainable argumentation, integrated with a commercial electronic health record (EHR) system in Serbia, a middle-income country in West Balkans.

Authors

  • Jesús Domínguez
    Department of Population Health Sciences King's College London London UK.
  • Denys Prociuk
    Imperial College London London UK.
  • Branko Marović
    University of Belgrade Belgrade Serbia.
  • Kristijonas Čyras
    Imperial College London London UK.
  • Oana Cocarascu
    Department of Informatics King's College London London UK.
  • Francis Ruiz
    London School of Hygiene and Tropical Medicine London UK.
  • Ella Mi
    University of Oxford Oxford UK.
  • Emma Mi
    University of Oxford Oxford UK.
  • Christian Ramtale
    Imperial College London London UK.
  • Antonio Rago
    Imperial College London London UK.
  • Ara Darzi
    Imperial College London London UK.
  • Francesca Toni
    Imperial College London London UK.
  • Vasa Curcin
    Department of Population Health Sciences King's College London London UK.
  • Brendan Delaney
    Imperial College London London UK.

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