Next Article in Journal
Charging Decision Optimization Strategy for Shared Autonomous Electric Vehicles Considering Multi-Objective Conflicts: An Integrated Solution Process Combining Multi-Agent Simulation Model and Genetic Algorithm
Previous Article in Journal
Strategic Decision-Making for Carbon Capture, Utilization, and Storage in Coal-Fired Power Plants: The Roles of Pollution Right Trading and Environmental Benefits
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

A Hybrid Approach to Developing Clinical Decision Support Systems for Treatment Planning and Monitoring

Institute of Automation and Control Processes Far Eastern Branch of the Russian Academy of Sciences (IACP FEB RAS), 5, Radio St., Vladivostok 690041, Russia
*
Author to whom correspondence should be addressed.
Systems 2025, 13(10), 920; https://doi.org/10.3390/systems13100920 (registering DOI)
Submission received: 19 August 2025 / Revised: 10 October 2025 / Accepted: 16 October 2025 / Published: 19 October 2025

Abstract

The development of clinical decision support systems for treatment planning and monitoring faces significant challenges, such as high labor intensity, integration complexities, lack of universality, and insufficient consideration of individual patient characteristics. This paper presents an innovative approach to overcoming these limitations, based on the creation of a specialized software toolkit. The key feature of the proposed approach is the use of a hybrid decision-making mechanism that integrates knowledge-based reasoning and case-based reasoning. For knowledge representation, a universal generalized ontology was developed, capable of modeling information about different treatment modalities (pharmacological, rehabilitative, surgical) while remaining independent of any specific medical specialty. This enabled the creation of a unified decision-making algorithm. For case retrieval, a combined method was proposed. The toolkit is being actively used on the IACPaaS platform to develop treatment planning systems across various medical domains, demonstrating its practical applicability and effectiveness.
Keywords: toolkit; clinical decision support system; ontology; case-based reasoning; knowledge base toolkit; clinical decision support system; ontology; case-based reasoning; knowledge base

Share and Cite

MDPI and ACS Style

Kovalev, R.; Gribova, V.; Okun, D. A Hybrid Approach to Developing Clinical Decision Support Systems for Treatment Planning and Monitoring. Systems 2025, 13, 920. https://doi.org/10.3390/systems13100920

AMA Style

Kovalev R, Gribova V, Okun D. A Hybrid Approach to Developing Clinical Decision Support Systems for Treatment Planning and Monitoring. Systems. 2025; 13(10):920. https://doi.org/10.3390/systems13100920

Chicago/Turabian Style

Kovalev, Roman, Valeriya Gribova, and Dmitry Okun. 2025. "A Hybrid Approach to Developing Clinical Decision Support Systems for Treatment Planning and Monitoring" Systems 13, no. 10: 920. https://doi.org/10.3390/systems13100920

APA Style

Kovalev, R., Gribova, V., & Okun, D. (2025). A Hybrid Approach to Developing Clinical Decision Support Systems for Treatment Planning and Monitoring. Systems, 13(10), 920. https://doi.org/10.3390/systems13100920

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop