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Automatic infection detection system.

Authors: Ove Granberg; Johan Gustav Bellika; Eirik Årsand; Gunnar Hartvigsen;

Automatic infection detection system.

Abstract

An infected person may be contagious already before the first symptoms appear. This person can, in the period of disease evolution, infect several associated citizens before consulting a general practitioner (GP). Early detection of contagion is therefore important to prevent spreading of diseases. The Automatic Infection Detection (AID) System faces this problem through investigating the hypothesis that the blood glucose (BG) level increases when a person is infected. The first objective of the prototyped version of the AID system was to identify possible BG elevations in the incubation time that could be related to the spread of infectious diseases. To do this, we monitored two groups of people, with and without diabetes mellitus. The AID system analyzed the results and we were able to detect two cases of infection during the study period. The time of detection occurred simultaneous or near the time of onset of symptoms. The detection did not occur earlier for a number of reasons. The most likely one is that the evolution process of an infectious disease is both complicated and involves the immune system and several organs in the body. The investigation with regard to isolating the key relations is therefore considered as a very complex study. Nevertheless, the AID system managed to detect the infection much earlier than what is possible with today's early warning systems for infectious diseases.

Related Organizations
Keywords

Blood Glucose, Giardiasis, Communicable Diseases, Disease Outbreaks, Population Surveillance, Diabetes Mellitus, Humans, Medical Informatics Applications, Monitoring, Physiologic

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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