Source:http://linkedlifedata.com/resource/pubmed/id/20082589
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
1
|
| pubmed:dateCreated |
2010-1-19
|
| pubmed:abstractText |
Continuous glucose monitoring (CGM) devices could be useful for real-time management of diabetes therapy. In particular, CGM information could be used in real time to predict future glucose levels in order to prevent hypo-/hyperglycemic events. This article proposes a new online method for predicting future glucose concentration levels from CGM data.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:chemical | |
| pubmed:status |
MEDLINE
|
| pubmed:month |
Jan
|
| pubmed:issn |
1557-8593
|
| pubmed:author | |
| pubmed:issnType |
Electronic
|
| pubmed:volume |
12
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
81-8
|
| pubmed:meshHeading |
pubmed-meshheading:20082589-Algorithms,
pubmed-meshheading:20082589-Biosensing Techniques,
pubmed-meshheading:20082589-Blood Glucose,
pubmed-meshheading:20082589-Equipment Design,
pubmed-meshheading:20082589-Humans,
pubmed-meshheading:20082589-Hydrogen-Ion Concentration,
pubmed-meshheading:20082589-Monitoring, Ambulatory,
pubmed-meshheading:20082589-Neural Networks (Computer),
pubmed-meshheading:20082589-Predictive Value of Tests
|
| pubmed:year |
2010
|
| pubmed:articleTitle |
Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring.
|
| pubmed:affiliation |
Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain. cperez@gbt.tfo.upm.es
|
| pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|