Monitoring Gestational Diabetes Mellitus with Cognitive Agents and Agent Environments

Authors:
Stefano Bromuri;Michael Ignaz Schumacher;Kostas Stathis;Juan Ruiz
Affiliations:
-;-;-;-
Venue:
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Year:
2011

Citing 8
Cited 3

A logic-based calculus of events

New Generation Computing
C-logic of complex objects

PODS '89 Proceedings of the eighth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Simply logical: intelligent reasoning by example

Simply logical: intelligent reasoning by example
Environment as a first class abstraction in multiagent systems

Autonomous Agents and Multi-Agent Systems
A metamodel for distributed event based systems

Proceedings of the second international conference on Distributed event-based systems
Pervasive Healthcare Computing: EMR/EHR, Wireless and Health Monitoring

Pervasive Healthcare Computing: EMR/EHR, Wireless and Health Monitoring
Distributed agent environments in the Ambient Event Calculus

Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
Towards distributed agent environments for pervasive healthcare

MATES'10 Proceedings of the 8th German conference on Multiagent system technologies

Agent based monitoring of gestational diabetes mellitus (demonstration)

Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
A self-healing distributed pervasive health system

International Journal of Web Engineering and Technology
COMMODITY12: A smart e-health environment for diabetes management

Journal of Ambient Intelligence and Smart Environments - Design and Deployment of Intelligent Environments

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an agent-based pervasive healthcare system (PHS) to support pregnant women with Gestational Diabetes Mellitus (GDM). Such an infrastructure uses a mobile application to monitor patients affected by GDM, whose parameters are then sent to and analysed by cognitive agents. We utilise a symbolic reasoning approach to formalise the events happening in the system, the entities participating in the interaction and the agent cognitive model for continuous monitoring of GDM. Such a cognitive model is based on deductive treatment adjustment rules to provide doctors with indications about the patient's treatment and on abductive rules to provide a diagnosis of the illness' current state. We evaluate our system by means of medical data to assess the precision of our infrastructure.