An adaptive network model for AI-assisted monitoring and management of neonatal respiratory distress

Nisrine Mokadem*, Fakhra Jabeen, Jan Treur, H. Rob Taal, Peter H.M.P. Roelofsma

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

This article presents the use of second-order adaptive network models of hospital teams consisting of doctors and nurses, interacting together. A variety of scenarios are modelled and simulated, in relation with respiratory distress of a neonate, along with the integration of an AI-Coach for monitoring and support of such teams and of organizational learning. The research highlights the benefits of introducing a virtual AI-Coach in a hospital setting. The practical application setting revolves around a medical team responsible for managing neonates with respiratory distress. In this setting an AI-Coach act as an additional team member, to ensure correct execution of medical procedure. Through simulation experiments, the adaptive network models demonstrate that the AI-Coach not only aids in maintaining correct medical procedure execution but also facilitates organizational learning, leading to significant improvements in procedure adherence and error reduction during neonatal care.

Original languageEnglish
Article number101231
JournalCognitive Systems Research
Volume86
DOIs
Publication statusPublished - 2024

Keywords

  • Adaptive network
  • AI-Coach
  • Hospital teams
  • Organizational learning
  • Respiratory distress

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