Back

Deep Learning-Enabled Screening of Chronic Kidney Disease from Echocardiography

2026-02-03 cardiovascular medicine Title + abstract only
View on medRxiv
Show abstract

Chronic kidney disease (CKD) affects nearly 850 million individuals globally; the prevalence of undiagnosed CKD is 60%. Taking advantage of the relationship between CKD and cardiovascular disease, we developed a deep learning (DL) model to detect CKD from parasternal long-axis (PLAX) videos using 325,377 PLAX videos from 62,818 patients at Cedars-Sinai Medical Center (CSMC). We externally validated our model in two independent cohorts of 2,224 patients at Stanford Healthcare (SHC) and 41,611 pat...

Predicted journal destinations

1
Scientific Reports
701 training papers
Top 2% 22.1%
2
PLOS ONE
1737 training papers
Top 66% 7.8%
3
Journal of the American Heart Association
92 training papers
Top 5% 6.4%
4
Frontiers in Cardiovascular Medicine
33 training papers
Top 4% 5.9%
5
Circulation
37 training papers
Top 4% 5.9%
6
European Heart Journal - Digital Health
15 training papers
Top 0.9% 3.8%
7
Nature Communications
483 training papers
Top 28% 3.8%
8
npj Digital Medicine
85 training papers
Top 8% 3.0%
9
Heart Rhythm
16 training papers
Top 3% 1.9%
10
Computers in Biology and Medicine
39 training papers
Top 4% 1.9%
11
The American Journal of Cardiology
15 training papers
Top 4% 1.9%
12
Circulation: Genomic and Precision Medicine
30 training papers
Top 5% 1.9%
13
Open Heart
18 training papers
Top 4% 1.9%
14
Hypertension
20 training papers
Top 2% 1.9%
15
eLife
262 training papers
Top 22% 1.9%
16
Nature Medicine
88 training papers
Top 5% 1.5%
17
Journal of Clinical Medicine
77 training papers
Top 14% 1.3%
18
EBioMedicine
21 training papers
Top 0.3% 1.3%
19
BMJ Open
553 training papers
Top 57% 1.3%
20
JAMA Network Open
125 training papers
Top 17% 1.3%
21
International Journal of Medical Informatics
25 training papers
Top 5% 1.2%
22
Journal of Biomedical Informatics
37 training papers
Top 5% 1.2%
23
Cureus
64 training papers
Top 13% 1.2%
24
Diabetologia
23 training papers
Top 2% 1.2%
25
Atherosclerosis
16 training papers
Top 5% 1.0%
26
Frontiers in Physiology
18 training papers
Top 3% 1.0%
27
PLOS Global Public Health
287 training papers
Top 34% 0.7%
28
PLOS Digital Health
88 training papers
Top 20% 0.7%