Comparison of regression methods for modeling intensive care length of stay.
about
Data Resource Profile: the Dutch National Intensive Care Evaluation (NICE) Registry of Admissions to Adult Intensive Care Units.Predicting hospital stay, mortality and readmission in people admitted for hypoglycaemia: prognostic models derivation and validation.An external validation of models to predict the onset of chronic kidney disease using population-based electronic health records from Salford, UK.Quantifying the effect of complications on patient flow, costs and surgical throughputsGuidelines on constructing funnel plots for quality indicators: A case study on mortality in intensive care unit patients.Operations research in intensive care unit management: a literature review.Associations of Polyethylenimine-Coated AN69ST Membrane in Continuous Renal Replacement Therapy with the Intensive Care Outcomes: Observations from a Claims Database from Japan.Random Survival Forests for Predicting the Bed Occupancy in the Intensive Care Unit.Vancomycin Combined With Clindamycin for the Treatment of Acute Bacterial Skin and Skin-Structure Infections.PICU Length of Stay: Factors Associated With Bed Utilization and Development of a Benchmarking Model.Predicting Length of Stay for Obstetric Patients via Electronic Medical Records.Predicting Length of Stay in Intensive Care Units after Cardiac Surgery: Comparison of Artificial Neural Networks and Adaptive Neuro-fuzzy System.The association between outcome-based quality indicators for intensive care units.Pre-kidney transplant lower extremity impairment and transplant length of stay: a time-to-discharge analysis of a prospective cohort study
P2860
Q31028868-3D19AEC3-01EF-4C61-9F46-FF7B12E60FFDQ33653750-0A853A62-4E11-460A-B9F6-BE726A66B430Q36073005-87D2E0BD-AC90-45EA-BBA4-9280D41EB7C1Q36171403-9F0361F1-CDF8-430C-88A7-C9A9782BFBDAQ38885698-13D68ADF-E944-4E39-88CA-2EAEBAA01DC2Q38926055-A00AC7AA-0798-45CA-93CE-910268C7E116Q38975214-E369E257-6C09-4B62-9400-35E3BC951005Q39210607-DD2F2B54-E1E3-4931-AFB6-10FEAD25F404Q40828569-5EBB5544-AAFA-4BFC-AF16-C53ED0CD65B9Q45956045-8B4D9AE6-47DF-40DD-A2D2-D3C37B52B3D1Q47219516-58103B5A-8DA3-4BBB-86A7-CA0E927CEDCFQ55247128-07ABF507-5B06-4C27-942B-EBB94A134825Q55335037-4A7F8425-2D49-4AAA-B65C-AE4480F46EA6Q57809423-1E48B39C-B352-469A-A330-A728BCA7FDC4
P2860
Comparison of regression methods for modeling intensive care length of stay.
description
2014 nî lūn-bûn
@nan
2014 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Comparison of regression methods for modeling intensive care length of stay.
@ast
Comparison of regression methods for modeling intensive care length of stay.
@en
Comparison of regression methods for modeling intensive care length of stay.
@nl
type
label
Comparison of regression methods for modeling intensive care length of stay.
@ast
Comparison of regression methods for modeling intensive care length of stay.
@en
Comparison of regression methods for modeling intensive care length of stay.
@nl
prefLabel
Comparison of regression methods for modeling intensive care length of stay.
@ast
Comparison of regression methods for modeling intensive care length of stay.
@en
Comparison of regression methods for modeling intensive care length of stay.
@nl
P2093
P2860
P1433
P1476
Comparison of regression methods for modeling intensive care length of stay.
@en
P2093
Evert de Jonge
Ilona W M Verburg
Nicolette F de Keizer
Niels Peek
P2860
P304
P356
10.1371/JOURNAL.PONE.0109684
P407
P577
2014-10-31T00:00:00Z