Towards data-driven personalised approach gestational is a M.Tech project topic for Computer Science & Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Towards data-driven personalised approach gestational Project Details
| Abstract |
Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy that involves the presence of high blood sugar levels that are usually found for the first time during pregnancy. Standard GDM management involves lifestyle changes and, potentially, medication. This practice involves the evaluation of self-monitored blood glucose levels, which is reported at intervals during clinic visits. However, existing paradigms of care, such as those found in Scotland, tend to be more labor-intensive and underutilize existing frameworks that combine risk stratification and digital health technologies. This thesis presents the first fully developed GDM care approach that is data-driven. The approach is focused on risk stratification of GDM patients
resulting in the need for remote insulin therapy to be supported by a digital platform for comprehensive remote monitoring. The approach is based on a mixed-methods methodology. From a quantitative perspective, the research aims to construct a predictive model with the highest possible accuracy for the prediction of insulin therapy. From a qualitative perspective, it involves the structured design of a digital solution to assist patients with self-management and clinicians with decision support to increase workflow in GDM care.
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| Reference Paper |
Towards a data-driven personalised approach to gestational diabetes care |
| Domain |
Computer Science |
| Sub-Domain |
Data Science & Big Data / Big Data Analytics |
| PDF Download |
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| Get Help |
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