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What is Data-Driven Modeling

Handbook of Research on Trends in the Diagnosis and Treatment of Chronic Conditions
Method used for either static or dynamic modeling, which is based on learning from the input and output data while disregarding explicit knowledge of the system’s physical behavior.
Published in Chapter:
Personal Health Systems for Diabetes Management, Early Diagnosis and Prevention
Konstantia Zarkogianni (National Technical University of Athens, Greece) and Konstantina S. Nikita (National Technical University of Athens, Greece)
DOI: 10.4018/978-1-4666-8828-5.ch022
Abstract
This chapter aims at the presentation and comparative assessment of tools and methodologies used for the development of Personal Health Systems (PHSs) for diabetes management, early diagnosis and prevention. Medical decision support systems such as glucose prediction models, risk assessment models for long-term diabetes complications, models for early diagnosis of diabetes and closed-loop glucose controllers along with integrated systems for diabetes management are described. The outcomes of a wide range of research studies demonstrate the feasibility of providing safe, reliable and cost-effective solutions towards improving patients' quality of life through the application of PHSs. Specific limitations that prevent these systems from being fully adopted in clinical practice are highlighted, while challenges and future research directions are summarized.
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