» Articles » PMID: 37048817

Artificial Intelligence in Cardiology: Why So Many Great Promises and Expectations, but Still a Limited Clinical Impact?

Overview
Journal J Clin Med
Specialty General Medicine
Date 2023 Apr 13
PMID 37048817
Authors
Affiliations
Soon will be listed here.
Abstract

Looking at the extremely large amount of literature, as summarized in two recent reviews on applications of Artificial Intelligence in Cardiology, both in the adult and pediatric age groups, published in the [...].

References
1.
Golany T, Radinsky K, Kofman N, Litovchik I, Young R, Monayer A . Physicians and Machine-Learning Algorithm Performance in Predicting Left-Ventricular Systolic Dysfunction from a Standard 12-Lead-Electrocardiogram. J Clin Med. 2022; 11(22). PMC: 9699306. DOI: 10.3390/jcm11226767. View

2.
Barbieri A, Albini A, Chiusolo S, Forzati N, Laus V, Maisano A . Three-Dimensional Automated, Machine-Learning-Based Left Heart Chamber Metrics: Associations with Prevalent Vascular Risk Factors and Cardiovascular Diseases. J Clin Med. 2022; 11(24). PMC: 9782505. DOI: 10.3390/jcm11247363. View

3.
Lee S, Lee S, Choi H, Lee J, Jeong Y, Kang D . Deep Learning Improves Prediction of Cardiovascular Disease-Related Mortality and Admission in Patients with Hypertension: Analysis of the Korean National Health Information Database. J Clin Med. 2022; 11(22). PMC: 9697313. DOI: 10.3390/jcm11226677. View

4.
Kroll L, Nassenstein K, Jochims M, Koitka S, Nensa F . Assessing the Role of Pericardial Fat as a Biomarker Connected to Coronary Calcification-A Deep Learning Based Approach Using Fully Automated Body Composition Analysis. J Clin Med. 2021; 10(2). PMC: 7832906. DOI: 10.3390/jcm10020356. View

5.
Kim J, Chae M, Chang H, Kim Y, Park E . Predicting Cardiac Arrest and Respiratory Failure Using Feasible Artificial Intelligence with Simple Trajectories of Patient Data. J Clin Med. 2019; 8(9). PMC: 6780058. DOI: 10.3390/jcm8091336. View