Graph-guided Gaussian Process-based Diagnosis of CVD Severity with Uncertainty Measures-Reference-Cited by-同舟云学术

Graph-guided Gaussian Process-based Diagnosis of CVD Severity with Uncertainty Measures

Published:2023-07-24 Issue: Volume: Page:
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Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Tassi Stavroula¹,Kigka Vassiliki¹,Siogkas Panagiotis¹,Rocchiccioli Silvia²,Pelosi Gualtriero²,Fotiadis Dimitrios I.³,Sakellarios Antonis I.³

Affiliation:

1. University of Ioannina,Unit of Medical Technology and Intelligent Information Systems,Department of Materials Science and Engineering,Ioannina,GR,Greece,45110

2. National Research Council,Institute of Clinical Physiology,Pisa,Italy,56124

3. University of Ioannina,Unit of Medical Technology and Intelligent Information Systems,Dept. of Materials Science and Engineering,Ioannina,GR,Greece,45110

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10340916.pdf?arnumber=10340916

Reference20 articles.

1. Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants

2. Detection of Cardiovascular Disease using Machine Learning Classification Models;Alalawi;International Journal of Engineering Research

3. Artificial Intelligence and Data Mining Methods for Cardiovascular Risk Prediction

4. A Multimodal Machine Learning Approach to Omics-Based Risk Stratification in Coronary Artery Disease

5. SmartFFR, a New Functional Index of Coronary Stenosis: Comparison With Invasive FFR Data

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