Towards Explainable General Medication Planning

Lee Or Alon, Hana Weitman, Alexander Shleyfman, Gal A. Kaminka

Research output: Contribution to journalConference articlepeer-review

Abstract

The ability to produce explanations for automated systems in healthcare domains is crucial for establishing trust between users and the system. Despite the growing demand for explainable artificial intelligence in medical domains, to the best of our knowledge, there are no existing works on explainability for medication planning. In this work, we propose a visualization method for medication planning domains to make the automatic planning process transparent to users, thereby fostering the desired trust.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume3831
StatePublished - 2024
Event1st Workshop on Explainable Artificial Intelligence for the Medical Domain, EXPLIMED 2024 - Santiago de Compostela, Spain
Duration: 20 Oct 2024 → …

Bibliographical note

Publisher Copyright:
© 2024 Copyright for this paper by its authors.

Keywords

  • Explainable AI Planning
  • Medication Planning
  • Personalized Medicine

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