| pubmed-article:19952726 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C0237401 | lld:lifeskim |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C0582175 | lld:lifeskim |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C0026336 | lld:lifeskim |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C1521970 | lld:lifeskim |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C0040223 | lld:lifeskim |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C0750572 | lld:lifeskim |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C0681842 | lld:lifeskim |
| pubmed-article:19952726 | lifeskim:mentions | umls-concept:C0029064 | lld:lifeskim |
| pubmed-article:19952726 | pubmed:issue | 1 | lld:pubmed |
| pubmed-article:19952726 | pubmed:dateCreated | 2009-12-24 | lld:pubmed |
| pubmed-article:19952726 | pubmed:abstractText | : Routine predictions made by surgeons or historical mean durations have only limited capacity to predict operating room (OR) time. The authors aimed to devise a prediction model using the surgeon's estimate and characteristics of the surgical team, the operation, and the patient. | lld:pubmed |
| pubmed-article:19952726 | pubmed:language | eng | lld:pubmed |
| pubmed-article:19952726 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:19952726 | pubmed:citationSubset | AIM | lld:pubmed |
| pubmed-article:19952726 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:19952726 | pubmed:month | Jan | lld:pubmed |
| pubmed-article:19952726 | pubmed:issn | 1528-1175 | lld:pubmed |
| pubmed-article:19952726 | pubmed:author | pubmed-author:EijkemansMari... | lld:pubmed |
| pubmed-article:19952726 | pubmed:author | pubmed-author:BoersmaEricE | lld:pubmed |
| pubmed-article:19952726 | pubmed:author | pubmed-author:SteyerbergEwo... | lld:pubmed |
| pubmed-article:19952726 | pubmed:author | pubmed-author:KazemierGeert... | lld:pubmed |
| pubmed-article:19952726 | pubmed:author | pubmed-author:NguyenTienT | lld:pubmed |
| pubmed-article:19952726 | pubmed:author | pubmed-author:van... | lld:pubmed |
| pubmed-article:19952726 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:19952726 | pubmed:volume | 112 | lld:pubmed |
| pubmed-article:19952726 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:19952726 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:19952726 | pubmed:pagination | 41-9 | lld:pubmed |
| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
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| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
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| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
| pubmed-article:19952726 | pubmed:meshHeading | pubmed-meshheading:19952726... | lld:pubmed |
| pubmed-article:19952726 | pubmed:year | 2010 | lld:pubmed |
| pubmed-article:19952726 | pubmed:articleTitle | Predicting the unpredictable: a new prediction model for operating room times using individual characteristics and the surgeon's estimate. | lld:pubmed |
| pubmed-article:19952726 | pubmed:affiliation | Department of Public Health, Center for Medical Decision Sciences, Erasmus MC University Medical Center, The Netherlands. m.j.c.eijkemans@umcutrecht.nl | lld:pubmed |
| pubmed-article:19952726 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:19952726 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
