Università degli Studi di Cagliari
Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization
Saba, Luca;
2022-01-01
Abstract
Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These techniques are ad-hoc, unreliable, not fully automated, and have variabilities. We, therefore, introduce AtheroEdge-MCDLAI (AE3.0DL) windows-based platform using multiclass Deep Learning (DL) system.
File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
| 1-s2.0-S0010482522007405-main.pdf Solo gestori archivio
Tipologia: versione editoriale
Dimensione 2.77 MB
Formato Adobe PDF
|
2.77 MB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.