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DiAbVi: IoT-based Recommender System for Diabetic Patients

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dc.contributor.author Lopez, Abegail Lyn
dc.date.accessioned 2019-08-16T17:23:13Z
dc.date.available 2019-08-16T17:23:13Z
dc.date.issued 2018-06
dc.identifier.uri http://dspace.cas.upm.edu.ph:8080/xmlui/handle/123456789/454
dc.description.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. en_US
dc.language.iso en en_US
dc.subject Diabetes en_US
dc.subject Insulin en_US
dc.subject Internet-of-Things en_US
dc.subject Recommender System en_US
dc.subject Teleconsultation en_US
dc.title DiAbVi: IoT-based Recommender System for Diabetic Patients en_US
dc.type Thesis en_US


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