Decision support systems (DSS) play an increasingly important role in medical practice. By assisting physicians in making clinical decisions and subsequent recommendations, medical DSS are expected to improve the quality of healthcare. The role of DSS in diabetes treatment and in particular in post clinical treatment by organizing an improved regime of food balance and patient diets is the target area of the study. Based on the Diabetes Mellitus Treatment Ontology (DMTO), the developed DSS for dietary recommendations for patients with diabetes mellitus is aimed at improvement of patient care. Having into account the clinical history and the lab test profiles of the patients, these diet recommendations are automatically inferred using the DMTO subontologies for patient’s lifestyle improvement and are based on reasoning on a set of newly developed production rules and the data from the patients records. The research presented in the paper is focused at intelligent integration of all data related to a particular patient and reasoning on them in order to generate personalized diet recommendations. A special-purpose knowledge base has been created, which enriches the DMTO with a set of original production rules and supports the elaboration of broader and more precise personalized dietary recommendations in the scope of the electronic health record services.
- Decision support system
- Semantic interoperability
- Knowledge base
- Type 2 diabetes mellitus
- Diet recommendation
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This research is supported by the National Scientific Program “eHealth”. Logistical support was received from the National Scientific Program “Information and Communication Technologies for a Single Digital Market in Science, Education and Security (ICTinSES)”.
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Nisheva-Pavlova, M., Mihaylov, I., Hadzhiyski, S., Vassilev, D. (2021). Ontology-Based Decision Support System for Dietary Recommendations for Type 2 Diabetes Mellitus. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12744. Springer, Cham. https://doi.org/10.1007/978-3-030-77967-2_61
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-77966-5
Online ISBN: 978-3-030-77967-2