Diabetes mellitus is a growing global disease which greatly affects each individual patient but also represents a global health burden with considerable financial impact on national health care systems. Currently applied therapeutic strategies are designed for a general use, but diabetes mellitus is very individual and the optimal therapy differs greatly among patients. Diabetes patients constantly encounter new drugs and technologies to better treat the disease and limit disease progression. This is a challenge for patients and diabetologists to select the most appropriate therapy and to properly adjust the parameters in complex therapies. New technologies such as automatic food and activity detection, lifestyle mHealth Apps and therapy pattern detection tools are currently emerging to support patients and diabetologists in their tasks.
In the publication„Towards Personalization of Diabetes Therapy Using Computerized Decision Support and Machine Learning: Some Open Problems and Challenges“relevant parameters for the personalization of diabetes therapy were identified and the role of decision support systems and machine learning are discussed.
Smart Health
Authors: Klaus Donsa, Stephan Spat, Peter Beck, Thomas R. Pieber, Andreas Holzinger
DOI: 10.1007/978-3-319-16226-3_10 In book: Smart Health, Chapter: 10, Publisher: Springer International Publishing, Editors: Andreas Holzinger, Carsten Röcker, Martina Ziefle, pp.237-260
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