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Authors: Bon Sy 1 ; 2 ; 3 ; Jin Chen 3 ; Magdalen Beiting-Parrish 1 ; 3 and Connor Brown 2

Affiliations: 1 Graduate Center/City University of NY, 365 5th Ave, NY 10016, U.S.A. ; 2 Queens College/City University of NY, 65-30 Kissena Blvd., Queens NY 11367, U.S.A. ; 3 SIPPA Solutions, 42-06A Bell Blvd., Queens NY 11361, U.S.A.

Keyword(s): Self-health Management, Behavioral Predictive Analytics.

Abstract: The objective of this research is to investigate the feasibility of applying behavioral predictive analytics to optimize diabetes self-management. In the U.S., less than 25% of patients actively engage in self-management even though self-management has been reported to associate with improved health outcomes and reduced healthcare costs. The proposed behavioral predictive analytics relies on manifold clustering to derive nonlinear clusters. These clusters are characterized by behavior readiness patterns for subpopulation segmentation. For each subpopulation, an individualized auto-regression model and a population-based model are developed to support self-management personalization in three areas: glucose self-monitoring, diet management, and exercise. The goal is to predict personalized activities that are most likely to achieve optimal engagement. This paper reports the result of manifold clusters based on 148 subjects with type 2 diabetes, and shows the preliminary result of perso nalization for 22 subjects under different scenarios. (More)

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Paper citation in several formats:
Sy, B.; Chen, J.; Beiting-Parrish, M. and Brown, C. (2021). Behavioral Predictive Analytics towards Personalization for Self-management. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - HEALTHINF; ISBN 978-989-758-490-9; ISSN 2184-4305, SciTePress, pages 111-121. DOI: 10.5220/0010231801110121

@conference{healthinf21,
author={Bon Sy. and Jin Chen. and Magdalen Beiting{-}Parrish. and Connor Brown.},
title={Behavioral Predictive Analytics towards Personalization for Self-management},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - HEALTHINF},
year={2021},
pages={111-121},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010231801110121},
isbn={978-989-758-490-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - HEALTHINF
TI - Behavioral Predictive Analytics towards Personalization for Self-management
SN - 978-989-758-490-9
IS - 2184-4305
AU - Sy, B.
AU - Chen, J.
AU - Beiting-Parrish, M.
AU - Brown, C.
PY - 2021
SP - 111
EP - 121
DO - 10.5220/0010231801110121
PB - SciTePress

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