|
covid-19 |
10 |
|
blood pressure variability |
8 |
|
atrial fibrillation |
7 |
|
heart failure |
7 |
|
mortality |
7 |
|
stroke |
7 |
|
all-cause mortality |
6 |
|
angiotensin receptor blockers |
6 |
|
angiotensinconverting enzyme inhibitors |
6 |
|
cancer |
6 |
|
cardiovascular mortality |
6 |
|
covid-19 incidence |
6 |
|
diabetes |
6 |
|
diabetes mellitus |
6 |
|
dipeptidyl peptidase-4 inhibitors |
6 |
|
intensive care unit |
6 |
|
intubation |
6 |
|
myocardial infarction |
6 |
|
sodium-glucose co-transporter |
6 |
|
sodium-glucose cotransporter-2 inhibitors |
6 |
|
cardiovascular disease |
5 |
|
electronic frailty index |
5 |
|
myocarditis |
5 |
|
myopericarditis |
5 |
|
pericarditis |
5 |
|
pulmonary hypertension |
5 |
|
random survival forest (rsf) |
5 |
|
renal complications |
5 |
|
risk stratification |
5 |
|
vaccine |
5 |
|
arrhythmias |
4 |
|
arrhythmogenic right ventricular cardiomyopathy/dysplasia |
4 |
|
association |
4 |
|
big data |
4 |
|
biostatistics |
4 |
|
brugada syndrome |
4 |
|
cardiac |
4 |
|
depolarization |
4 |
|
dipeptidyl peptidase-4 inhibitors, diabetes mellitus |
4 |
|
dpp4 |
4 |
|
ecg |
4 |
|
edoxaban |
4 |
|
electronic health records |
4 |
|
epidemiology |
4 |
|
fracture |
4 |
|
hip fracture |
4 |
|
latent variable |
4 |
|
machine learning |
4 |
|
metformin |
4 |
|
neutrophil-to-lymphocyte ratio |
4 |
|
nonnegative matrix factorization |
4 |
|
osteoporotic |
4 |
|
predictive model |
4 |
|
proton pump inhibition |
4 |
|
repolarization |
4 |
|
risk factors |
4 |
|
risk score |
4 |
|
risk stratification, dementia |
4 |
|
sglt2 |
4 |
|
sulphonylurea |
4 |
|
syncope |
4 |
|
tachycardia |
4 |
|
ventricular |
4 |
|
ventricular arrhythmias |
4 |
|
ventricular fibrillation |
4 |
|
ventricular tachycardia |
4 |
|
vertebral fracture |
4 |
|
warfarin |
4 |
|
acquired long qt syndrome |
3 |
|
action potential duration |
3 |
|
alzheimer's disease |
3 |
|
anti-diabetic drugs |
3 |
|
automated ecg |
3 |
|
brugada |
3 |
|
cognitive dysfunction |
3 |
|
cohort study |
3 |
|
crystalline arthropathy |
3 |
|
decision tree |
3 |
|
deep learning |
3 |
|
dementia |
3 |
|
detrended fluctuation analysis |
3 |
|
dpp4 inhibitor |
3 |
|
entropy |
3 |
|
genetic variants |
3 |
|
gout |
3 |
|
heptanol |
3 |
|
icd (implantable cardioverter-defibrillator) |
3 |
|
index of electrophysiological balance |
3 |
|
inter-atrial block |
3 |
|
long qt syndrome |
3 |
|
longitudinal strain;mechanical dispersion |
3 |
|
metabolic syndrome |
3 |
|
mitral regurgitation |
3 |
|
mitral stenosis |
3 |
|
mitral valve |
3 |
|
myocardial repolarization |
3 |
|
neutrophil |
3 |
|
non-negative matrix factorization |
3 |
|
p-wave |
3 |
|
p-wave area |
3 |
|
p-wave duration |
3 |
|
parkinson's disease |
3 |
|
prognostic nutritional index |
3 |
|
random survival forest |
3 |
|
random survival forests |
3 |
|
retrospective study |
3 |
|
risk stratificacion |
3 |
|
sglt2 (sodium-glucose cotransporter 2) inhibitor |
3 |
|
speckle-tracking echocardiography |
3 |
|
strain |
3 |
|
sudden cardiac death |
3 |
|
t –t interval peak end |
3 |
|
temporal |
3 |
|
variability |
3 |
|
ventricular tachiarrhythmias |
3 |
|
anti-diabetic medication |
2 |
|
anxiety |
2 |
|
asian |
2 |
|
catecholaminergic polymorphic ventricular tachycardia |
2 |
|
classification |
2 |
|
cpvt |
2 |
|
crisis communication |
2 |
|
depression |
2 |
|
domain knowledge |
2 |
|
emotional responses |
2 |
|
factorization machine |
2 |
|
fragmented qrs |
2 |
|
fuzzy partition |
2 |
|
fuzzy set theory |
2 |
|
gender differences |
2 |
|
generalized anxiety disorder |
2 |
|
genetics |
2 |
|
hcru |
2 |
|
healthcare |
2 |
|
inflammation |
2 |
|
insulin resistance |
2 |
|
locally weighting |
2 |
|
mendelian randomization |
2 |
|
myocardial fibrosis |
2 |
|
neuro-inflammation |
2 |
|
non-alzheimer's dementia |
2 |
|
readmission prediction |
2 |
|
risk prediction |
2 |
|
ryr2 |
2 |
|
sglt2 inhibitor |
2 |
|
social media |
2 |
|
triglyceride-glucose index |
2 |
|
type 2 diabetes |
2 |
|
vascular |
2 |
|
ventricular arrhythmia |
2 |
|
visit-to-visit blood pressure variability |
2 |
|
ai-assisted precision medicine |
1 |
|
artificial intelligence |
1 |
|
bankruptcy control |
1 |
|
bayesian optimal design |
1 |
|
chronic obstructive pulmonary disease |
1 |
|
computational education |
1 |
|
copd |
1 |
|
corticosteroids |
1 |
|
credibility theory |
1 |
|
data analytics |
1 |
|
data science in education |
1 |
|
dea |
1 |
|
decision making |
1 |
|
deep neural networks |
1 |
|
driving behaviour |
1 |
|
driving performance |
1 |
|
dynamic programming |
1 |
|
electricity price |
1 |
|
exponential random graph model |
1 |
|
forecasting |
1 |
|
fuzzy bilevel programming |
1 |
|
fuzzy semientropy |
1 |
|
granular computing |
1 |
|
graph neural network |
1 |
|
hazardous material |
1 |
|
health management |
1 |
|
heuristic algorithm |
1 |
|
implementation |
1 |
|
implicit enumeration algorithm |
1 |
|
mean-entropy model |
1 |
|
mean-semi-entropy model |
1 |
|
medical image processing |
1 |
|
multi objective programming |
1 |
|
multi-period portfolio optimization |
1 |
|
multi-period portfolio selection |
1 |
|
multimodal learning |
1 |
|
network science |
1 |
|
nsga ii |
1 |
|
observational |
1 |
|
occupational burnout |
1 |
|
pneumonia detection |
1 |
|
portfolio selection |
1 |
|
primary care |
1 |
|
r-vine copula |
1 |
|
reliability |
1 |
|
risk aversion factor |
1 |
|
risk model |
1 |
|
road smoothness |
1 |
|
rolling optimization |
1 |
|
semi-entropy |
1 |
|
smart travel |
1 |
|
social networks |
1 |
|
spatial dependence |
1 |
|
step stress accelerated degradation testing |
1 |
|
teachers' professional development |
1 |
|
teaching performance |
1 |
|
teaching ratings |
1 |
|
transaction costs |
1 |
|
transparent logistics |
1 |
|
travel itinerary problem |
1 |
|
travel scheme planning |
1 |
|
urban path planning |
1 |
|
vehicle routing problem |
1 |
