Comparison between logistic regression and neural networks to predict death in patients with suspected sepsis in the emergency room.
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Artificial neural networks as prediction tools in the critically ill.A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery - part I: model planning.Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models.Prediction of malignant breast lesions from MRI features: a comparison of artificial neural network and logistic regression techniques.Development and performance of a diagnostic/prognostic scoring system for breakthrough painA Comparison of Intensive Care Unit Mortality Prediction Models through the Use of Data Mining TechniquesA multivariate Bayesian model for assessing morbidity after coronary artery surgery.Predictive modeling in pediatric traumatic brain injury using machine learning.Comparison of logistic regression and artificial neural network in low back pain prediction: second national health survey.Year in review 2005: Critical Care - resource management.Predicting Health Care Utilization After Behavioral Health Referral Using Natural Language Processing and Machine LearningThe pathogenesis of sepsis.Artificial neural networks versus bivariate logistic regression in prediction diagnosis of patients with hypertension and diabetes.Artificial neural network, genetic algorithm, and logistic regression applications for predicting renal colic in emergency settings.In Silico Modeling in Infectious Disease.Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China.Development and validation of an improved neurological hemifield test to identify chiasmal and postchiasmal lesions by automated perimetry.Using what you get: dynamic physiologic signatures of critical illness.Prediction of periventricular leukomalacia. Part II: Selection of hemodynamic features using computational intelligenceModeling a neural network as a teaching tool for the learning of the structure-function relationship.
P2860
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P2860
Comparison between logistic regression and neural networks to predict death in patients with suspected sepsis in the emergency room.
description
2005 nî lūn-bûn
@nan
2005 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2005 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2005年の論文
@ja
2005年論文
@yue
2005年論文
@zh-hant
2005年論文
@zh-hk
2005年論文
@zh-mo
2005年論文
@zh-tw
2005年论文
@wuu
name
Comparison between logistic re ...... d sepsis in the emergency room
@nl
Comparison between logistic re ...... sepsis in the emergency room.
@ast
Comparison between logistic re ...... sepsis in the emergency room.
@en
type
label
Comparison between logistic re ...... d sepsis in the emergency room
@nl
Comparison between logistic re ...... sepsis in the emergency room.
@ast
Comparison between logistic re ...... sepsis in the emergency room.
@en
prefLabel
Comparison between logistic re ...... d sepsis in the emergency room
@nl
Comparison between logistic re ...... sepsis in the emergency room.
@ast
Comparison between logistic re ...... sepsis in the emergency room.
@en
P2093
P2860
P921
P356
P1433
P1476
Comparison between logistic re ...... d sepsis in the emergency room
@en
P2093
Carlos Martínez
Diego Alvarez
Jorge Farbiarz
P2860
P2888
P304
P356
10.1186/CC3054
P407
P50
P577
2005-02-17T00:00:00Z
P5875
P6179
1025844891