Intelligent self-organizing microservice composition using hybrid learning for neonatal ward

Title

Intelligent self-organizing microservice composition using hybrid learning for neonatal ward

Creator

Poornima, Sharon; Immanuel, Ashok V.

Description

This research presents an innovative self-organizing microservice composition model specifically tailored for dynamic and time-sensitive healthcare environments such as neonatal intensive care units (NICU). A hybrid machine learning classifier detects neonatal conditions and assigns treatment plans based on real-time vitals. The composition process is guided by a deep learning agent that combines unsupervised and reinforcement learning to develop intelligent bonding strategies. Microservices act as autonomous agents, supporting decentralized service choreography within the self-organizing framework. The bonding strategies of direct bonding and shared bonding are implemented for single conditions and coexisting conditions, respectively. The simulation results are based on actual NICU data, demonstrating the ability of the model to dynamically compose services while ensuring optimal resource utilization. The model demonstrates an adaptive and dynamic composition through emergence and continuous learning for changing clinical conditions, and demonstrates emergent behavior through reinforcement learning. The model's predictive capabilities enable anticipatory service loading, providing context-aware treatment in critical healthcare scenarios. This self-organizing architecture model offers a scalable and robust solution for autonomous, decentralized service choreography in critical healthcare environments. This is an open access article under the CC BY-SA license https://creativecommons.org/licenses/by-sa/4.0/.

Source

IAES International Journal of Artificial Intelligence;Volume;15;Issue;2;pp.1097-1108

Date

01-01-2026

Publisher

Institute of Advanced Engineering and Science

Subject

Critical care; Health care; Hybrid learning; Microservice composition; Self-organization

Coverage

Poornima S., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India; Immanuel A.V., Department of Computer Science, CHRIST (Deemed to be University), Bengaluru, India

Rights

All Open Access; Gold Open Access

Relation

ISSN: 20894872;

Format

online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijai.v15.i2.pp1097-1108

https://www.scopus.com/pages/publications/105036029784?origin=resultslist