Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population
Article
[키워드] Albert Einstein
analysed
Analysis
ANN
Area
artificial
Artificial Neural Network (ANN)
AUC
basophil
Blood
blood tests
Brazil
can be used
changes in
characteristic
Clinical data
collected
common cold
Community
Complete
condition
conditions
count
COVID-19
Curve
dataset
decrease
develop
Diagnosis
diagnostic
early stage
eosinophils
flexible
full blood count
Health
high accuracy
hospital
identify
immune response
IMPROVE
increase in
individuals
Infection
initial screening
intelligence
knowledge
leukocytes
linear combination
Lymphocytes
machine learning
MERS
methodology
monocyte
Monocytes
novel coronavirus SARS-CoV-2
overlap
pandemic
parameter
Patient
PCR
Platelets
Population
practitioners
predict
prediction
random
receiver operating characteristics
researcher
SARS-CoV-2
SARS-COV-2 infection
SARS-CoV-2 patient
SARS-CoV-2 positive patient
SARS-CoV-2 positive patients
Screening
Standard deviation
statistical test
Symptom
the SARS-CoV-2
while
[DOI] 10.1016/j.intimp.2020.106705 PMC 바로가기 [Article Type] Article
[DOI] 10.1016/j.intimp.2020.106705 PMC 바로가기 [Article Type] Article