Interpretable Data-Driven Approach Based on Feature Selection Methods and GAN-Based Models for Cardiovascular Risk Prediction in Diabetic Patients
Author:
Affiliation:
1. Department of Signal Theory and Communications, Telematics and Computing, Rey Juan Carlos University, Fuenlabrada, Madrid, Spain
2. Norwegian Centre for E-Health Research, University Hospital of North Norway, Tromsø, Norway
Funder
European Commission
European Project WARIFA
Spanish Government
Community of Madrid with the European Social Fund through the Youth Employment Operational Program and the Youth Employment Initiative
Rey Juan Carlos University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/6287639/10380310/10552854.pdf?arnumber=10552854
Reference84 articles.
1. IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045
2. IDF Diabetes Atlas: Global estimates of the prevalence of diabetes for 2011 and 2030
3. Cardiovascular risk assessment in prediabetic patients in a hypertensive population: The role of cystatin C
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