Literature DB >> 19964403

Data mining for blood glucose prediction and knowledge discovery in diabetic patients: the METABO diabetes modeling and management system.

Eleni Georga1, Vasilios Protopappas, Alejandra Guillen, Giuseppe Fico, Diego Ardigo, Maria Teresa Arredondo, Themis P Exarchos, Demosthenes Polyzos, Dimitrios I Fotiadis.   

Abstract

METABO is a diabetes monitoring and management system which aims at recording and interpreting patient's context, as well as, at providing decision support to both the patient and the doctor. The METABO system consists of (a) a Patient's Mobile Device (PMD), (b) different types of unobtrusive biosensors, (c) a Central Subsystem (CS) located remotely at the hospital and (d) the Control Panel (CP) from which physicians can follow-up their patients and gain also access to the CS. METABO provides a multi-parametric monitoring system which facilitates the efficient and systematic recording of dietary, physical activity, medication and medical information (continuous and discontinuous glucose measurements). Based on all recorded contextual information, data mining schemes that run in the PMD are responsible to model patients' metabolism, predict hypo/hyper-glycaemic events, and provide the patient with short and long-term alerts. In addition, all past and recently-recorded data are analyzed to extract patterns of behavior, discover new knowledge and provide explanations to the physician through the CP. Advanced tools in the CP allow the physician to prescribe personalized treatment plans and frequently quantify patient's adherence to treatment.

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Year:  2009        PMID: 19964403     DOI: 10.1109/IEMBS.2009.5333635

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  7 in total

1.  Mobile Monitoring Framework to Design Parameterized and Personalized m-Health Applications According to the Patient's Diseases.

Authors:  Vladimir Villarreal; Ramon Hervas; Jesus Fontecha; Jose Bravo
Journal:  J Med Syst       Date:  2015-08-29       Impact factor: 4.460

2.  A Clinical Support System Based on Quality of Life Estimation.

Authors:  Brígida Mónica Faria; Joaquim Gonçalves; Luis Paulo Reis; Álvaro Rocha
Journal:  J Med Syst       Date:  2015-08-16       Impact factor: 4.460

3.  Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring.

Authors:  K Zarkogianni; K Mitsis; E Litsa; M-T Arredondo; G Ficο; A Fioravanti; K S Nikita
Journal:  Med Biol Eng Comput       Date:  2015-06-07       Impact factor: 2.602

4.  Evaluation of short-term predictors of glucose concentration in type 1 diabetes combining feature ranking with regression models.

Authors:  Eleni I Georga; Vasilios C Protopappas; Demosthenes Polyzos; Dimitrios I Fotiadis
Journal:  Med Biol Eng Comput       Date:  2015-03-15       Impact factor: 2.602

Review 5.  A Systematic Review for Mobile Monitoring Solutions in M-Health.

Authors:  Vladimir Villarreal; Ramón Hervás; José Bravo
Journal:  J Med Syst       Date:  2016-07-27       Impact factor: 4.460

Review 6.  Diabetes self-management arrangements in Europe: a realist review to facilitate a project implemented in six countries.

Authors:  Antonis A Kousoulis; Evridiki Patelarou; Sue Shea; Christina Foss; Ingrid A Ruud Knutsen; Elka Todorova; Poli Roukova; Mari Carmen Portillo; María J Pumar-Méndez; Agurtzane Mujika; Anne Rogers; Ivaylo Vassilev; Manuel Serrano-Gil; Christos Lionis
Journal:  BMC Health Serv Res       Date:  2014-10-02       Impact factor: 2.655

7.  Design and Development of Diabetes Management System Using Machine Learning.

Authors:  Robert A Sowah; Adelaide A Bampoe-Addo; Stephen K Armoo; Firibu K Saalia; Francis Gatsi; Baffour Sarkodie-Mensah
Journal:  Int J Telemed Appl       Date:  2020-07-16
  7 in total

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