Title: Towards Personalization of Diabetes Therapy Using Computerized Decision Support and Machine Learning
Lecturer: Klaus DONSA <expertise> and Stephan SPAT <expertise>
Abstract: Diabetes mellitus (DM) is a growing global disease which highly affects the individual patient and represents a global health burden with financial impact on national health care systems. The therapeutic options include lifestyle changes such as change of diet and an increase of physical activity, but also administration of oral or injectable antidiabetic drugs. The diabetes therapy, especially with insulin, is complex. Therapy decisions include various medical and life-style related information. Computerized decision support systems (CDSS) aim to improve the treatment process in patient´s self-management but also in institutional care. Therefore, the personalization of the patient´s diabetes treatment is possible at different levels and is also facilitated by using new therapy aids like food and activity recognition systems, lifestyle support tools and pattern recognition for insulin therapy optimization. In this talk we discuss the role of machine learning in this context. Furthermore we provide insights in different strategies to personalize diabetes therapy and how CDSS can support the therapy process. During our work we found open problems and challenges for the personalization of diabetes therapy. In a final discussion we will address these open problems with focus on decision support systems and especially machine learning technology.