AI Enabled Healthcare Services During Cross-Border Medical Emergency and Regular Patient Services (ESCORT project): System architecture and first results in Emergency Medicine Scenario

Authors

  • George Floros Aristotle University of Thessaloniki https://orcid.org/0000-0002-2867-9604
  • Daniele Gui Universita Cattolica Del Sacro Cuore
  • Sabina Magalini Universita Cattolica Del Sacro Cuore
  • Maurizio Martignano Universita Cattolica Del Sacro Cuore
  • Incinur Zellhuber Cosinuss GmbH
  • Michael Weber Cosinuss GmbH
  • Themistoklis Anagnostopoulos Netcompany-Intrasoft SA
  • Filopoimin Lykokanellos Netcompany-Intrasoft SA
  • Sofia Tsekeridou Netcompany-Intrasoft SA
  • Savvas Petanidis Aristotle University of Thessaloniki https://orcid.org/0000-0001-7482-6559
  • Krishna Chandramouli Rinicom Limited https://orcid.org/0000-0001-5850-9799
  • Garik Markarian Rinicom Limited

DOI:

https://doi.org/10.59297/ferb2m71

Keywords:

Artificial Intelligence (AI), Machine learning (ML), European Health Emergency Preparedness and Response Authority (HERA), Internet of Things (IoT), Emergency Medicine, Chronic Diseases, Emerging Pathogens

Abstract

The ESCORT project (ESCORT Project, 2024) aims at connecting up-to-date IoT Wearables, Artificial Intelligence and Machine Learning towards building a framework for a better cross border response for medical emergencies and public health protection and resilience. The ESCORT project brings together healthcare providers from five European member states and one associated member Israel specialized in emergency medicine and offering regular health and care services. New and better integrated digital services have been designed in consultation with stakeholders including patients, patient advocacy groups, health and care service professionals and providers. This paper presents a detailed outline of the project goals and ambitions supplemented by the requirements considered in the development of the overall platform architecture. Out of the 10 tools identified for integration in the project, two will be further elaborated with initial requirements that have been collected, and a first analysis of the solutions will be presented.

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Published

2025-08-03

How to Cite

Floros, G., Gui, D., Magalini, S., Martignano, M., Zellhuber, I., Weber, M., Anagnostopoulos, T., Lykokanellos, F., Tsekeridou, S. ., Petanidis, S., Chandramouli, K., & Markarian, G. (2025). AI Enabled Healthcare Services During Cross-Border Medical Emergency and Regular Patient Services (ESCORT project): System architecture and first results in Emergency Medicine Scenario. Proceedings of the International ISCRAM Conference. https://doi.org/10.59297/ferb2m71

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