Using Docker service containers to build browser-based clinical decision support systems (CDSS)

Kopytov G.V., Drozdov A.N.
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The article presents a technology for building clinical decision support systems (CDSS) based on service containers using Docker and a web interface that runs directly in the browser without installing specialized software on workstation of a clinician. A modular architecture is proposed in which each application module is packaged as an independent service container combining a lightweight web server, a user interface, and computational components for medical image processing. Communication between the browser and the server side is implemented via a persistent bidirectional WebSocket connection with binary message serialization (MessagePack), which provides low latency and efficient transfer of large data. For local storage of images and analysis of results, browser facilities (IndexedDB with the Dexie.js wrapper) are used to speed up repeated data access. Three-dimensional visualization and basic operations with DICOM data are implemented with Three.js and AMI.js: this toolchain supports the integration of interactive elements arising from the task context (annotations, landmarks, markers, 3D models) into volumetric medical images.

Server components and functional modules are assembled as a set of interacting containers managed by Docker. The paper discusses the choice of base images, approaches to minimizing containers down to runtime-only executables without external utilities, and the organization of multi-stage builds with a dedicated build container. It describes a hub service that launches application containers on user request, performs request proxying, manages sessions, and switches a container from shared to exclusive mode at the start of computations. Examples of application modules are provided (fractional flow reserve estimation, quantitative flow ratio computation, aortic valve closure modeling), along with the integration of a React-based interface with a three-dimensional scene, a versioning policy, automated reproducibility checks, and the deployment procedure on the target platform.

It is demonstrated that containerization ensures portability and reproducibility of the software environment, dependency isolation and scalability, while the browser-based interface provides accessibility, reduced infrastructure requirements, and interactive real-time visualization of medical data. Technical limitations are noted (dependence on versions of visualization libraries and data formats) together with practical mitigation measures.

Keywords: clinical decision support systems (CDSS), zero-footprint applications, service containers, web application
Citation in English: Kopytov G.V., Drozdov A.N. Using Docker service containers to build browser-based clinical decision support systems (CDSS) // Computer Research and Modeling, 2026, vol. 18, no. 1, pp. 133-147
Citation in English: Kopytov G.V., Drozdov A.N. Using Docker service containers to build browser-based clinical decision support systems (CDSS) // Computer Research and Modeling, 2026, vol. 18, no. 1, pp. 133-147
DOI: 10.20537/2076-7633-2026-18-1-133-147
URL: http://crm-en.ics.org.ru/journal/article/3692/
Creative Commons License This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

Copyright © 2026 Kopytov G.V., Drozdov A.N.

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