ArticleBiomedical engineering online2015
Differential sequential patterns supporting insulin therapy of new-onset type 1 diabetes.
Article in Biomedical engineering online, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Prescription pattern analysis of Type 2 Diabetes Mellitus: a cross-sectional study in Isfahan, Iran.BioData mining · 2023Article
- Machine Learning and Data Mining Methods in Diabetes Research.Computational and structural biotechnology journal · 2017Review
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Authors and funding
3 authors.
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Abstract
backgroundIn spite of numerous research efforts on supporting the therapy of diabetes mellitus, the subject still involves challenges and creates active interest among researchers. In this paper, a decision support tool is presented for setting insulin therapy in new-onset type 1 diabetes.
methodsThe concept of differential sequential patterns (DSPs) is introduced with the aim of representing deviations in the patient's blood glucose level (BGL) and the amount of insulin injections administered. The decision support tool is created using data mining algorithms for discovering sequential patterns.
resultsBy using the DSPs, it is possible to support the physician's decisionmaking concerning changing the treatment (i.e., whether to increase or decrease the insulin dosage). The other contributions of the paper are an algorithm for generating DSPs and a new method for evaluating nocturnal glycaemia. The proposed qualitative evaluation of nocturnal glycaemia improves the generalization capabilities of the DSPs.
conclusionsThe usefulness of the proposed approach was evident in the results of experiments in which juvenile diabetic patients actual data were used. It was confirmed that the proposed DSPs can be used to guide the therapy of numerous juvenile patients with type 1 diabetes.
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