Back

Automated assessment of chest CT severity scores in patients suspected of COVID-19 infection

2022-12-30 radiology and imaging Title + abstract only
View on medRxiv
Show abstract

BackgroundThe COVID-19 pandemic has claimed numerous lives in the last three years. With new variants emerging every now and then, the world is still battling with the management of COVID-19. PurposeTo utilize a deep learning model for the automatic detection of severity scores from chest CT scans of COVID-19 patients and compare its diagnostic performance with experienced human readers. MethodsA deep learning model capable of identifying consolidations and ground-glass opacities from the ches...

Predicted journal destinations

1
Scientific Reports
701 training papers
#1 40.0%
2
PLOS ONE
1737 training papers
Top 38% 17.9%
3
Diagnostics
36 training papers
Top 0.4% 3.4%
4
Computers in Biology and Medicine
39 training papers
Top 2% 3.4%
5
PLOS Digital Health
88 training papers
Top 8% 2.4%
6
npj Digital Medicine
85 training papers
Top 10% 1.9%
7
Journal of Clinical Medicine
77 training papers
Top 13% 1.4%
8
Nature Communications
483 training papers
Top 45% 1.4%
9
Scientific Data
30 training papers
Top 2% 1.2%
10
NeuroImage
36 training papers
Top 5% 1.2%
11
Heliyon
57 training papers
Top 6% 1.2%
12
Frontiers in Oncology
34 training papers
Top 5% 1.2%
13
eLife
262 training papers
Top 49% 0.9%
14
Imaging Neuroscience
18 training papers
Top 2% 0.9%
15
Human Brain Mapping
53 training papers
Top 9% 0.9%
16
Cureus
64 training papers
Top 18% 0.9%
17
Cancers
57 training papers
Top 8% 0.9%
18
Medicine
29 training papers
Top 5% 0.9%
19
BMJ Open
553 training papers
Top 70% 0.6%
20
European Respiratory Journal
44 training papers
Top 5% 0.6%
21
BMC Cancer
21 training papers
Top 6% 0.6%
22
Journal of Medical Internet Research
81 training papers
Top 23% 0.6%
23
Nature Medicine
88 training papers
Top 24% 0.6%
24
NeuroImage: Clinical
77 training papers
Top 14% 0.6%
25
PeerJ
46 training papers
Top 10% 0.6%
26
Frontiers in Medicine
99 training papers
Top 28% 0.6%