Deep extracted features to support Content-Based Image Retrieval systems in the diagnosis of Covid-19 and Interstitial diseases
International Journal of Computer Assisted Radiology and Surgery
; 17(SUPPL 1):S13-S14, 2022.
Article
in English
| EMBASE | ID: covidwho-1926067
ADAM protein; endogenous compound; adult; autoencoder; conference abstract; controlled study; convolutional neural network; coronavirus disease 2019; cross validation; deep learning; diagnosis; differential diagnosis; digital imaging and communications in medicine; dimensionality reduction; entropy; feature extraction; female; human; image retrieval; interstitial lung disease; k nearest neighbor; major clinical study; male; middle aged; neighborhood; nerve cell; principal component analysis; radiologist; retrospective study; side effect; thorax radiography; X ray
Full text:
Available
Collection:
Databases of international organizations
Database:
EMBASE
Type of study:
Diagnostic study
/
Experimental Studies
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Language:
English
Journal:
International Journal of Computer Assisted Radiology and Surgery
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS