Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.
about
Measuring changes in transmission of neglected tropical diseases, malaria, and enteric pathogens from quantitative antibody levels.Interpreting Hemoglobin A1C in Combination With Conventional Risk Factors for Prediction of Cardiovascular Risk.Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the WardsEvaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury.Using Active Learning for Speeding up Calibration in Simulation Models.Using electronic health record collected clinical variables to predict medical intensive care unit mortality.Machine Learning and Decision Support in Critical Care.Learning a Severity Score for Sepsis: A Novel Approach based on Clinical Comparisons.Patient length of stay and mortality prediction: A survey.Online cross-validation-based ensemble learning.Sequential Organ Failure Assessment Score Modified for Recent Infection in Patients With Hematologic Malignant Tumors and Severe Sepsis.Data-Adaptive Estimation for Double-Robust Methods in Population-Based Cancer Epidemiology: Risk differences for lung cancer mortality by emergency presentation.Automatic recognition of symptom severity from psychiatric evaluation records.Computational health economics for identification of unprofitable health care enrollees.Prediction of absolute risk of acute graft-versus-host disease following hematopoietic cell transplantation.Understanding intensive care unit benchmarking.Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay.Predicting Mortality in Diabetic ICU Patients Using Machine Learning and Severity Indices.Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality.An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest
P2860
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P2860
Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.
description
2014 nî lūn-bûn
@nan
2014 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի նոյեմբերին 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
Mortality prediction in intens ...... LA): a population-based study.
@ast
Mortality prediction in intens ...... LA): a population-based study.
@en
type
label
Mortality prediction in intens ...... LA): a population-based study.
@ast
Mortality prediction in intens ...... LA): a population-based study.
@en
prefLabel
Mortality prediction in intens ...... LA): a population-based study.
@ast
Mortality prediction in intens ...... LA): a population-based study.
@en
P2093
P2860
P1476
Mortality prediction in intens ...... LA): a population-based study.
@en
P2093
Marco Carone
Mark J van der Laan
Matthieu Resche Rigon
Maya L Petersen
Romain Pirracchio
P2860
P356
10.1016/S2213-2600(14)70239-5
P577
2014-11-24T00:00:00Z