Monitoring Gestational Diabetes

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Monitoring Gestational Diabetes Applied Intelligent Systems Lab 29th of November 2012 – TheArk eHealth event aislab.hevs.ch Dr. Stefano Bromuri, Johannes Krampf, Dr René Schumann, Prof. Dr. Michael Schumacher

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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.

Transcript of Monitoring Gestational Diabetes

Page 1: Monitoring Gestational Diabetes

Monitoring Gestational Diabetes Applied Intelligent Systems Lab 29th of November 2012 – TheArk eHealth event aislab.hevs.ch Dr. Stefano Bromuri, Johannes Krampf, Dr René Schumann, Prof. Dr. Michael Schumacher

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G-DEMANDE: Monitoring Gestational 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

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Problems in current Care

1.  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.

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Mobile data acquisition

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o  Incoming physiological patient data is a)  Stored in a database b)  Forwarded to an expert system analyzing the data

Pervasive Health System

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Expert System (Golem)

o  An expert agent is monitoring the condition of one patient…

o  … and reasoning on its values

o  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.

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Medical knowledge representation

Described rules (abductive & deductive) for the agents.

Abductive Rules Example

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Feasibility tests within CHUV hospital

o  Started in November 2012 for a period of 6-9 months with 12 patients

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Applied Intelligent Systems Lab (2009-2012)

o  Chronic disease monitoring o  eHealth interoperability standards o  Medical data analysis o  Medical decision support o  (in the future: Healthcare coordination)