Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging, and Test Data: Diagnostic Model Development
증상, 영상 및 테스트 데이터에서 SARS-CoV-2 감염 위험 계산: 진단 모델 개발
Original Paper
[키워드] Accuracy
assist
Bayesian
Bayesian inference
be positive
Cancer
cardiovascular disease
Care
center
Chain Reaction
changes in
clinical evaluation
clinically
clinician
common
Comorbidity
computation
computing
consecutive patient
consecutive patients
continuum
cough
Course
COVID-19
decision
develop
development
diabete
diabetes
diagnose
Diagnosis
diagnostic
diagnostic test
Diego
female
Fever
Health
help
hospital
hospital care
hypertension
imaging
Infection
informatics
Laboratory
Laboratory test
Local
location
machine learning
machine learning model
Model
molecular
nucleic acid
nucleic acid testing
objective
Patient
patient symptom
Patient symptoms
patients
patients with SARS-CoV-2
polymerase chain reaction
positive
presenting
Prevalence
Probability
profile
repeated
Result
reverse transcription
Reverse transcription-polymerase chain reaction
risk
RT-PCR
SARS-CoV-2
SARS-COV-2 infection
sensitivities
sensitivity
Specificities
specificity
Support
Symptom
Test
Test statistics
tested
trained model
University of California
[DOI] 10.2196/24478 PMC 바로가기 [Article Type] Original Paper
[DOI] 10.2196/24478 PMC 바로가기 [Article Type] Original Paper