| no |
title |
author |
magazine |
year |
volume |
issue |
page(s) |
type |
| 1 |
A complexity evaluation system for mitral valve repair based on preoperative echocardiographic and machine learning
|
Zhu, Kun
|
|
|
81 |
C |
p. 25-37
|
article
|
| 2 |
Clinical phenotypes and outcomes of patients with left ventricular thrombus: an unsupervised cluster analysis
|
Leow, Aloysius S.T.
|
|
|
81 |
C |
p. 65-74
|
article
|
| 3 |
Deep learning for cardiac imaging: focus on myocardial diseases, a narrative review
|
Tsampras, Theodoros
|
|
|
81 |
C |
p. 18-24
|
article
|
| 4 |
Designing medical artificial intelligence systems for global use: focus on interoperability, scalability, and accessibility
|
Oikonomou, Evangelos K.
|
|
|
81 |
C |
p. 9-17
|
article
|
| 5 |
Detection and classification of electrocardiography using hybrid deep learning models
|
Selvam, Immaculate Joy
|
|
|
81 |
C |
p. 75-84
|
article
|
| 6 |
Digital twins: reimagining the future of cardiovascular risk prediction and personalised care
|
Dziopa, Katarzyna
|
|
|
81 |
C |
p. 4-8
|
article
|
| 7 |
From algorithms to clinical outcomes: how artificial intelligence shapes metaclinical medicine
|
Vardas, Panos E.
|
|
|
81 |
C |
p. 1-3
|
article
|
| 8 |
Intelligent diagnosis of Kawasaki disease from real-world data using interpretable machine learning models
|
Duan, Yifan
|
|
|
81 |
C |
p. 38-48
|
article
|
| 9 |
Unraveling phenotypic heterogeneity in stanford type B aortic dissection patients through machine learning clustering analysis of cardiovascular CT imaging
|
Liu, Kun
|
|
|
81 |
C |
p. 49-64
|
article
|
Journal description