A Personalized Recommendation System to Support Diabetes Self-Management for American Indians
| Autor: | Juan Li, Vikram Pandey, Shadi Alian |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Gerontology
self-management Food intake medicine.medical_specialty General Computer Science Diabetes self management 02 engineering and technology Recommender system Body weight 0202 electrical engineering electronic engineering information engineering medicine General Materials Science ontology Socioeconomic status logic Personal care diabetes Public health General Engineering 020206 networking & telecommunications Clinical diabetes American Indian reasoning 020201 artificial intelligence & image processing lcsh:Electrical engineering. Electronics. Nuclear engineering Psychology lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 6, Pp 73041-73051 (2018) |
| ISSN: | 2169-3536 |
| Popis: | The epidemic of diabetes in American Indian (AI) communities is a serious public health challenge. The incidence and prevalence of diabetes have increased dramatically with accompanying increases in body weight and diminished physical activity. In this paper, we propose a proactive diabetes self-care recommendation system specifically for AI patients. It recommends healthy life style to users to fight for their diabetes. Thanks to the quasi-ubiquitous use of cellphones in most AI tribes, we choose cellphones as the platform to provide smart personal care for AI patients. By integrating the AI users’ ontological profile with general clinical diabetes recommendation and guidelines, the system can make personalized recommendations (e.g., food intake and physical workout) based on the special socioeconomic, cultural, and geographical status particularly to AI patients. The proposed system was implemented as mobile applications. Evaluations performed by use case studies and human expert verification demonstrate the effectiveness of the system. |
| Databáze: | OpenAIRE |
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