Cargando…
Coronary artery decision algorithm trained by two-step machine learning algorithm
A two-step machine learning (ML) algorithm for estimating both fractional flow reserve (FFR) and decision (DEC) for the coronary artery is introduced in this study. The primary purpose of this model is to suggest the possibility of ML-based FFR to be more accurate than the FFR calculation technique...
Autores principales: | Kim, Young Woo, Yu, Hee-Jin, Kim, Jung-Sun, Ha, Jinyong, Choi, Jongeun, Lee, Joon Sang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048707/ https://www.ncbi.nlm.nih.gov/pubmed/35492670 http://dx.doi.org/10.1039/c9ra08999c |
Ejemplares similares
-
Electrocardiogram-based deep learning algorithm for the screening of obstructive coronary artery disease
por: Choi, Seong Huan, et al.
Publicado: (2023) -
Outcome-Based Decision-Making Algorithm for Treating Patients with Primary Aldosteronism
por: Kim, Jung Hee, et al.
Publicado: (2022) -
Machine learning algorithms for predicting mortality after coronary artery bypass grafting
por: Khalaji, Amirmohammad, et al.
Publicado: (2022) -
A review on machine learning algorithms for the ionic liquid chemical space
por: Koutsoukos, Spyridon, et al.
Publicado: (2021) -
A machine learning–based clinical decision support algorithm for reducing unnecessary coronary angiograms
por: Schwalm, J.D., et al.
Publicado: (2021)