Artificial Intelligence for Cardiothoracic Imaging: Overview of Current and Emerging Applications.
Journal
Seminars in roentgenology
ISSN: 1558-4658
Titre abrégé: Semin Roentgenol
Pays: United States
ID NLM: 0053252
Informations de publication
Date de publication:
Apr 2023
Apr 2023
Historique:
received:
01
02
2023
accepted:
02
02
2023
medline:
25
4
2023
pubmed:
23
4
2023
entrez:
22
04
2023
Statut:
ppublish
Résumé
Artificial intelligence algorithms can learn by assimilating information from large datasets in order to decipher complex associations, identify previously undiscovered pathophysiological states, and construct prediction models. There has been tremendous interest and increased incorporation of artificial intelligence into various industries, including healthcare. As a result, there has been an exponential rise in the number of research articles and industry participants producing models intended for a variety of applications in medical imaging, which can be challenging to navigate for radiologists. In thoracic imaging, multiple applications are being evaluated for chest radiography and computed tomography and include applications for lung nodule evaluation and cancer imaging, quantifying diffuse lung disorders, and cardiac imaging, to name a few. This review aims to provide an overview of current clinical AI models, focusing on the most common clinical applications of AI in cardiothoracic imaging.
Identifiants
pubmed: 37087139
pii: S0037-198X(23)00008-1
doi: 10.1053/j.ro.2023.02.001
pii:
doi:
Types de publication
Review
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
184-195Informations de copyright
Copyright © 2023 Elsevier Inc. All rights reserved.