<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>We propose a decision support framework (DSF) assisting insulin therapy of diabetic children. Our DSF relies on a medical treatment graph (MTG), which models and graphically represents clinical pathways. Using the MTG, it is possible to plan and adapt medical decisions dependent upon the current health state of a patient and the progress of the treatment. Our MTG fits well with the requirements of clinical practice. The presented work is a cooperative effort of researchers in computer science and medicine. The MTG model has been thoroughly tested and validated using real-world clinical data. The usefulness of the approach has been confirmed by physicians.</p>
</abstract>

We propose a decision support framework (DSF) assisting insulin therapy of diabetic children. Our DSF relies on a medical treatment graph (MTG), which models and graphically represents clinical pathways. Using the MTG, it is possible to plan and adapt medical decisions dependent upon the current health state of a patient and the progress of the treatment. Our MTG fits well with the requirements of clinical practice. The presented work is a cooperative effort of researchers in computer science and medicine. The MTG model has been thoroughly tested and validated using real-world clinical data. The usefulness of the approach has been confirmed by physicians.

Mining clinical pathways for daily insulin therapy of diabetic children

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Mining clinical pathways for daily insulin therapy of diabetic children"}

We propose a decision support framework (DSF) assisting insulin therapy of diabetic children. Our DSF relies on a medical treatment graph (MTG), which models...

Mining clinical pathways for daily insulin therapy of diabetic children

Online veröffentlicht: 03. Apr. 2021

Seitenbereich: 107 - 121

Eingereicht: 18. März 2020

Akzeptiert: 17. Okt. 2020

DOI: https://doi.org/10.34768/amcs-2021-0008

Schlüsselwörter
decision support systems, modeling clinical pathways, diabetes mellitus

© 2021 Rafal Deja et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mining clinical pathways for daily insulin therapy of diabetic children

Online veröffentlicht: 03. Apr. 2021

Seitenbereich: 107 - 121

Eingereicht: 18. März 2020

Akzeptiert: 17. Okt. 2020

DOI: https://doi.org/10.34768/amcs-2021-0008

Schlüsselwörterdecision support systems, modeling clinical pathways, diabetes mellitus

© 2021 Rafal Deja et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
decision support systems, modeling clinical pathways, diabetes mellitus