Disease Insights Through Analysis: Using machine learning to provide feedback in the MONARCA system

Mads Frost; Afsaneh Doryab; Jakob Bardram

7th International Conference on Pervasive Computing Technologies for Healthcare

Research Article

Disease Insights Through Analysis: Using machine learning to provide feedback in the MONARCA system

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Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/icst.pervasivehealth.2013.252071,
    author={Mads Frost and Afsaneh Doryab and Jakob Bardram},
    title={Disease Insights Through Analysis: Using machine learning to provide feedback in the MONARCA system},
    proceedings={7th International Conference on Pervasive Computing Technologies for Healthcare},
    publisher={IEEE},
    proceedings_a={PERVASIVEHEALTH},
    year={2013},
    month={5},
    keywords={healthcare bipolar disorder monitoring system machine learning feedback system},
    doi={10.4108/icst.pervasivehealth.2013.252071}
}

Mads Frost
Afsaneh Doryab
Jakob Bardram
Year: 2013
Disease Insights Through Analysis: Using machine learning to provide feedback in the MONARCA system
PERVASIVEHEALTH
ICST
DOI: 10.4108/icst.pervasivehealth.2013.252071

Mads Frost¹^,*, Afsaneh Doryab², Jakob Bardram¹

1: IT University of Copenhagen
2: Carnegie Mellon University

*Contact email: madsf@itu.dk

Abstract

There is currently a growing interest in personal health technologies using data collection strategies to develop context-aware systems. The insights from this data could help patients and clinicians monitor and manage mental illness. We describe our approach to support the data analysis and feedback to clinicians and patients through extending the MONARCA Self- Assessment System.

Keywords: healthcare bipolar disorder monitoring system machine learning feedback system

Published: 2013-05-23
Publisher: IEEE

: http://dx.doi.org/10.4108/icst.pervasivehealth.2013.252071