A multi-view vision transformer integrated with progressive transfer learning for accurate identification of prenatal fetal coarctation of the aorta
- 21 July 2026
- journal article
- Published by Elsevier in Engineering Applications of Artificial Intelligence
- Vol. 181
Abstract
No abstract availableFunding Information
- National Natural Science Foundation of China (82502485)
- Major Projects of Guangdong Education Department for Foundation Research and Applied Research (2024A1515220146)
- Basic and Applied Basic Research Foundation of Guangdong Province
- Ministry of Science and Technology of the People's Republic of China (2021ZD0200500)
This publication has 25 references indexed in Scilit:
- Strategically annotating rare disease samples to improve semi-supervised learning in long-tailed medical image classificationBiomedical Signal Processing and Control, 2025
- Role of artificial‐intelligence‐assisted automated cardiac biometrics in prenatal screening for coarctation of aortaUltrasound in Obstetrics & Gynecology, 2024
- Deep‐learning model for prenatal congenital heart disease screening generalizes to community setting and outperforms clinical detectionUltrasound in Obstetrics & Gynecology, 2024
- Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre studyEuropean Journal of Radiology, 2020
- Neonatal management of prenatally suspected coarctation of the aortaPrenatal Diagnosis, 2020
- State-of-the-Art Deep Learning in Cardiovascular Image AnalysisJACC: Cardiovascular Imaging, 2019
- Congenital Heart Disease: Causes, Diagnosis, Symptoms, and TreatmentsCell Biochemistry and Biophysics, 2015
- Hypoplasia, Pseudocoarctation and Coarctation of the Aorta – A Systematic ReviewHeart, Lung and Circulation, 2015
- Simplifying ultrasound assessment of the fetal heart: Incorporating the complete Three Vessel View into routine screeningAustralasian Journal of Ultrasound in Medicine, 2013
- Prevalence of Congenital Heart Defects in Metropolitan Atlanta, 1998-2005The Journal of Pediatrics, 2008