Data analysis
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Principal Investigators
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Further Members
Description:
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Analysis of the effects of intelligent assistance systems on the quality of life
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Quantifying the benefits of complex interventions compared to the already established PRISM app
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Data modeling using latent change, multi-level and multi-group models
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Prediction of successful aging using machine learning approaches
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Identifying predictors of successful aging through automated tracking and health monitoring
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Detecting critical moments of change in the participants continuously surveyed activity inside and outside their homes
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Main Result:
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Individualized prognosis of intelligent assistive systems effectiveness in SMART-AGE based on facilitating as well as inhibiting factors on the personal and environmental level