Please use this identifier to cite or link to this item: http://dspace.cas.upm.edu.ph:8080/xmlui/handle/123456789/454
Title: DiAbVi: IoT-based Recommender System for Diabetic Patients
Authors: Lopez, Abegail Lyn
Keywords: Diabetes
Insulin
Internet-of-Things
Recommender System
Teleconsultation
Issue Date: Jun-2018
Abstract: Diabetes is a group of metabolic diseases characterized by high blood sugar levels over a prolonged period. Currently, rural areas in the Philippines lack recommender systems that can guide nurses in recommending a treatment plan for Diabetes. Also, in some scenarios where nurses conduct home visits, existing glucometer devices do not have the ability to automatically map the blood glucose levels to the corresponding patient. Consequently, this study aims a nurse in the rural health unit to use an "IoT Glucometer", which can communicate with the DiAbVi System that recommends an insulin regimen. More importantly, there is an integrated teleconsultation system in it intended for the medical doctors in the urban to monitor the recommendations of the system to a patient. In this manner, the DiAbVi System helps to guide diabetic patients in the rural areas in the eff ective management of Diabetes.
URI: http://dspace.cas.upm.edu.ph:8080/xmlui/handle/123456789/454
Appears in Collections:Computer Science SP

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