Monitoring Gestational Diabetes

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Le Valais est un terreau fertile pour le développement du eHealth. En effet, les savoir-faire dans les domaines de la santé et des technologies de l’information (ICT) y sont très développés. Le Forum The Ark du 29 novembre a été l’occasion de présenter ces savoir-faire. A cette occasion, Prof. Dr Michael Schumacher a présenté G-DEMANDE.

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Monitoring Gestational Diabetes

  1. 1. Monitoring Gestational DiabetesApplied Intelligent Systems Lab29th of November 2012 – TheArk eHealth eventaislab.hevs.chDr. Stefano Bromuri, Johannes Krampf, Dr René Schumann,Prof. Dr. Michael Schumacher
  2. 2. G-DEMANDE: MonitoringGestational Diabetes Mellitus o  Gestational diabetes mellitus (GDM) is a condition that affects 2-5% of all the pregnancies and manifests itself with high blood sugar levels during pregnancy. o  It can cause health problems for mother and child like, n  Preeclampsia, Eclampsia, n  Hyperglycemia, n  Macrosomia, and n  Diabetes type II 2
  3. 3. Problems in current Care1.  Current treatment practices: Doctors usually see patient 2-3 times a week. In case of hyperglycemia, the patient may arrive too late.2.  At each patient visit, the doctor sees the glucose levels and blood pressure at the very moment of the consultancy, and not the evolution of the values. 3
  4. 4. Mobile data acquisition 4
  5. 5. Pervasive Health Systemo  Incoming physiological patient data is a)  Stored in a database b)  Forwarded to an expert system analyzing the data 5
  6. 6. Expert System (Golem)o  An expert agent is monitoring the condition of one patient…o  … and reasoning on its valueso  To scale-up the agents can be: n  distributed to different nodes; n  activated and deactivated by a balancer; n  persisted in an agent database. 6
  7. 7. Medical knowledge representation Abductive Rules Example Described rules (abductive & deductive) for the agents. 7
  8. 8. 8
  9. 9. Feasibility tests within CHUV hospitalo  Started in November 2012 for a period of 6-9 months with 12 patients 12
  10. 10. Applied Intelligent Systems Lab (2009-2012)o  Chronic disease monitoringo  eHealth interoperability standardso  Medical data analysiso  Medical decision supporto  (in the future: Healthcare coordination) 13

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