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Consort diagram of the training dataset (CRD):

Lakshya Singhal (11478546) ; Yash Garg (11478549) ; Philip Yang (11478552)...
https://figshare.com/articles/figure/Consort_diagram_of_the_training_dataset_CRD_/16678887. , 2021

Link: https://doi.org/10.1371/journal.pone.0257056.s001

RT Journal
T1 <Title>Consort diagram of the training dataset (CRD)</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_16678887&Exemplar=1&LAN=DE
				
A1 Lakshya Singhal (11478546)
A1 Yash Garg (11478549)
A1 Philip Yang (11478552)
A1 Azade Tabaie (11436346)
A1 A. Ian Wong (11478555)
A1 Akram Mohammed (3477728)
A1 Lokesh Chinthala (11478558)
A1 Dipen Kadaria (11478561)
A1 Amik Sodhi (11478564)
A1 Andre L. Holder (11478567)
A1 Annette Esper (6385298)
A1 James M. Blum (7300496)
A1 Robert L. Davis (11478570)
A1 Gari D. Clifford (6508535)
A1 Greg S. Martin (9155149)
A1 Rishikesan Kamaleswaran (10176173)
YR 2021
K1 Cell Biology
K1 Genetics
K1 Science Policy
K1 Mental Health
K1 Biological Sciences not elsewhere classified
K1 Information Systems not elsewhere classified
K1 systolic blood pressure
K1 performed significantly better
K1 maximum respiratory rate
K1 machine learning algorithm
K1 intensive care units
K1 generate predictive models
K1 electronic medical record
K1 94 ])
K1 compared
K1 92 &# 8211
K1 19 emr database
K1 88 – 0
K1 75 – 0
K1 085 – 0
K1 identified salient features
K1 18 &# 8211
K1 younger age group
K1 older age group
K1 div >< p
K1 81 &# 8211
K1 comprising 899 covid
K1 90 )
K1 sensitivity
K1 19 </ p
K1 81 – 0
K1 predicting covid19 patients
K1 berlin clinical criteria
K1 berlin criteria
K1 19 patients
K1 sbp )
K1 important features
K1 clinical data
K1 18 years
K1 804 patients
K1 predicting ards
K1 site covid
K1 observational window
K1 moderate groups
K1 identify risk
K1 female groups
K1 emory healthcare
K1 data collected
K1 center validation
JF https://figshare.com/articles/figure/Consort_diagram_of_the_training_dataset_CRD_/16678887
LK http://dx.doi.org/https://doi.org/10.1371/journal.pone.0257056.s001
DO https://doi.org/10.1371/journal.pone.0257056.s001
SF ELIB - SuUB Bremen

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