AI Article Synopsis

  • - The CAPABLE project developed a multi-agent system to assist cancer patients and their clinicians by providing coaching advice and decision support based on clinical guidelines.
  • - A Case Manager (CM) orchestrates the agents' activities by monitoring patient data on a shared blackboard and using a special syntax inspired by HL7-FHIR for effective communication.
  • - The CM has been validated through simulations and is essential for coordinating the agents, with potential applications for integrating various healthcare services into a seamless telemedicine system.

Article Abstract

Background: Within the CAPABLE project the authors developed a multi-agent system that relies on a distributed architecture. The system provides cancer patients with coaching advice and supports their clinicians with suitable decisions based on clinical guidelines.

Objectives: As in many multi-agent systems we needed to coordinate the activities of all agents involved. Moreover, since the agents share a common blackboard where all patients' data are stored, we also needed to implement a mechanism for the prompt notification of each agent upon addition of new information potentially triggering its activation.

Methods: The communication needs have been investigated and modeled using the HL7-FHIR (Health Level 7-Fast Healthcare Interoperability Resources) standard to ensure proper semantic interoperability among agents. Then a syntax rooted in the FHIR search framework has been defined for representing the conditions to be monitored on the system blackboard for activating each agent.

Results: The Case Manager (CM) has been implemented as a dedicated component playing the role of an orchestrator directing the behavior of all agents involved. Agents dynamically inform the CM about the conditions to be monitored on the blackboard, using the syntax we developed. The CM then notifies each agent whenever any condition of interest occurs. The functionalities of the CM and other actors have been validated using simulated scenarios mimicking the ones that will be faced during pilot studies and in production.

Conclusion: The CM proved to be a key facilitator for properly achieving the required behavior of our multi-agent system. The proposed architecture may also be leveraged in many clinical contexts for integrating separate legacy services, turning them into a consistent telemedicine framework and enabling application reusability.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10499504PMC
http://dx.doi.org/10.1055/a-2113-4443DOI Listing

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