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

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.