Source:http://linkedlifedata.com/resource/pubmed/id/21048960
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
10
|
| pubmed:dateCreated |
2010-11-4
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| pubmed:abstractText |
Obesity is unanimously regarded as a global epidemic and a major contributing factor to the development of many common illnesses. Laparoscopic Adjustable Gastric Banding (LAGB) is one of the most popular surgical approaches worldwide. Yet, substantial variability in the results and significant rate of failure can be expected, and it is still debated which categories of patients are better suited to this type of bariatric procedure. The aim of this study was to build a statistical model based on both psychological and physical data to predict weight loss in obese patients treated by LAGB, and to provide a valuable instrument for the selection of patients that may benefit from this procedure.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:issn |
1932-6203
|
| pubmed:author |
pubmed-author:AnselminoMarcoM,
pubmed-author:CalderoneAlbaA,
pubmed-author:CassanoGiovanni BattistaGB,
pubmed-author:DBB,
pubmed-author:FierabracciPaolaP,
pubmed-author:LandiAlbertoA,
pubmed-author:LippiChitaC,
pubmed-author:MaffeiMargheritaM,
pubmed-author:PiaggiPaoloP,
pubmed-author:PincheraAldoA,
pubmed-author:SantiniFerruccioF,
pubmed-author:VittiPaoloP
|
| pubmed:issnType |
Electronic
|
| pubmed:volume |
5
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
e13624
|
| pubmed:meshHeading |
pubmed-meshheading:21048960-Adult,
pubmed-meshheading:21048960-Female,
pubmed-meshheading:21048960-Gastric Bypass,
pubmed-meshheading:21048960-Humans,
pubmed-meshheading:21048960-Middle Aged,
pubmed-meshheading:21048960-Neural Networks (Computer),
pubmed-meshheading:21048960-Obesity,
pubmed-meshheading:21048960-Treatment Outcome
|
| pubmed:year |
2010
|
| pubmed:articleTitle |
Artificial neural networks in the outcome prediction of adjustable gastric banding in obese women.
|
| pubmed:affiliation |
Department of Electrical Systems and Automation, University of Pisa, Pisa, Italy. paolo.piaggi@gmail.com
|
| pubmed:publicationType |
Journal Article
|