ArticleScientific reports2019
A Deep Learning Framework for Design and Analysis of Surgical Bioprosthetic Heart Valves.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 60 citations in OpenAlex.
- Circular RNA-mediated regulation of key signaling pathways in cardiovascular diseases: a review.Journal of advanced research · 2026Review
- ValveFit: An analysis-suitable B-spline-based surface fitting framework for patient-specific modeling of tricuspid valves.Computer methods in applied mechanics and engineering · 2026Article
- Artificial Intelligence in Transcatheter Aortic Valve Replacement: Its Current Role and Ongoing Challenges.Diagnostics (Basel, Switzerland) · 2024Review
- Artificial Intelligence in the Screening, Diagnosis, and Management of Aortic Stenosis.Reviews in cardiovascular medicine · 2024Review
- Latest Developments in Adapting Deep Learning for Assessing TAVR Procedures and Outcomes.Journal of clinical medicine · 2023Review
- Few-shot deep learning for AFM force curve characterization of single-molecule interactions.Patterns (New York, N.Y.) · 2023Article
- Perfect prosthetic heart valve: generative design with machine learning, modeling, and optimization.Frontiers in bioengineering and biotechnology · 2023Article
- A Review of Digital Health and Biotelemetry: Modern Approaches towards Personalized Medicine and Remote Health Assessment.Journal of personalized medicine · 2022Review
- Clinical Applications of Artificial Intelligence-An Updated Overview.Journal of clinical medicine · 2022Review
- Study of Biomechanics of the Heart Valve Leaflet Apparatus Using Numerical Simulation Method.Sovremennye tekhnologii v meditsine · 2022Article
- Parameterization, geometric modeling, and isogeometric analysis of tricuspid valves.Computer methods in applied mechanics and engineering · 2021Article
- Cardiovascular Stents: A Review of Past, Current, and Emerging Devices.Materials (Basel, Switzerland) · 2021Review
- Intelligent Calibration of Static FEA Computations Based on Terrestrial Laser Scanning Reference.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Bioprosthetic heart valves (BHVs) are commonly used as heart valve replacements but they are prone to fatigue failure; estimating their remaining life directly from medical images is difficult. Analyzing the valve performance can provide better guidance for personalized valve design. However, such analyses are often computationally intensive. In this work, we introduce the concept of deep learning (DL) based finite element analysis (DLFEA) to learn the deformation biomechanics of bioprosthetic aortic valves directly from simulations. The proposed DL framework can eliminate the time-consuming biomechanics simulations, while predicting valve deformations with the same fidelity. We present statistical results that demonstrate the high performance of the DLFEA framework and the applicability of the framework to predict bioprosthetic aortic valve deformations. With further development, such a tool can provide fast decision support for designing surgical bioprosthetic aortic valves. Ultimately, this framework could be extended to other BHVs and improve patient care.
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Registered trials
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