Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Hooman Vaseli

Showing results (1-10 of 5) with videos related to

Pageof 1
Sort By:
IEEE Transactions on Medical Imaging|December 17, 2019
On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality AssessmentZhibin Liao, Hany Girgis, Amir Abdi, et al.
Medical Image Analysis|May 5, 2025
ProtoASNet: Comprehensive evaluation and enhanced performance with uncertainty estimation for aortic stenosis classification in echocardiographyAng Nan Gu, Hooman Vaseli, Michael Y Tsang, et al.
IEEE Transactions on Medical Imaging|September 12, 2025
MultiASNet: Multimodal Label Noise Robust Framework for the Classification of Aortic Stenosis in EchocardiographyVictoria Wu, Andrea Fung, Bahar Khodabakhshian, et al.
The International Journal of Cardiovascular Imaging|August 10, 2024
Assessment of left ventricular wall thickness and dimension: accuracy of a deep learning model with prediction uncertaintyJeffrey Yim, Mobina Mahdavi, Hooman Vaseli, et al.
Diseases (Basel, Switzerland)|February 23, 2024
Automated Atrial Fibrillation Diagnosis by Echocardiography without ECG: Accuracy and Applications of a New Deep Learning ApproachNelson Lu, Hooman Vaseli, Mobina Mahdavi, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Medical Imaging|December 17, 2019
On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality AssessmentZhibin Liao, Hany Girgis, Amir Abdi, et al.
Medical Image Analysis|May 5, 2025
ProtoASNet: Comprehensive evaluation and enhanced performance with uncertainty estimation for aortic stenosis classification in echocardiographyAng Nan Gu, Hooman Vaseli, Michael Y Tsang, et al.
IEEE Transactions on Medical Imaging|September 12, 2025
MultiASNet: Multimodal Label Noise Robust Framework for the Classification of Aortic Stenosis in EchocardiographyVictoria Wu, Andrea Fung, Bahar Khodabakhshian, et al.
The International Journal of Cardiovascular Imaging|August 10, 2024
Assessment of left ventricular wall thickness and dimension: accuracy of a deep learning model with prediction uncertaintyJeffrey Yim, Mobina Mahdavi, Hooman Vaseli, et al.
Diseases (Basel, Switzerland)|February 23, 2024
Automated Atrial Fibrillation Diagnosis by Echocardiography without ECG: Accuracy and Applications of a New Deep Learning ApproachNelson Lu, Hooman Vaseli, Mobina Mahdavi, et al.
Pageof 1