Cover Image

From Motion to Meaning: Biomechanics-Informed Neural Network for Explainable Cardiovascular Disease Identification

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Valentin, Comte, Piella, Gemma, Ceresa, Mario, Ballester, Miguel A. Gonzalez
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Data-Centric Label Smoothing for Explainable Glaucoma Screening from Eye Fundus Images
by: Galdran, Adrian, et al.
Published: (2024)

Trainable and Explainable Simplicial Map Neural Networks
by: Paluzo-Hidalgo, Eduardo, et al.
Published: (2023)

Explainable Machine Learning Framework for Cardiovascular Disease Diagnosis and Prognosis
by: Sourov, Md. Emon Akter, et al.
Published: (2025)

Dissipative Latent Residual Physics-Informed Neural Networks for Modeling and Identification of Electromechanical Systems
by: Long, Youyuan, et al.
Published: (2026)

Parallelizing Node-Level Explainability in Graph Neural Networks
by: Llorente, Oscar, et al.
Published: (2026)

Machine Learning Models for the Identification of Cardiovascular Diseases Using UK Biobank Data
by: Islam, Sheikh Mohammed Shariful, et al.
Published: (2024)

PETIMOT: A Novel Framework for Inferring Protein Motions from Sparse Data Using SE(3)-Equivariant Graph Neural Networks
by: Lombard, Valentin, et al.
Published: (2025)

Hidden Conflicts in Neural Networks and Their Implications for Explainability
by: Dejl, Adam, et al.
Published: (2023)

Optimization Trade-offs in Asynchronous Federated Learning: A Stochastic Networks Approach
by: Alahyane, Abdelkrim, et al.
Published: (2026)

Iterative Training of Physics-Informed Neural Networks with Fourier-enhanced Features
by: Wu, Yulun, et al.
Published: (2025)

Dynamical Mean-Field Theory of Self-Attention Neural Networks
by: Poc-López, Ángel, et al.
Published: (2024)

Deeply Explainable Artificial Neural Network
by: Zucker, David
Published: (2025)

Seeking Interpretability and Explainability in Binary Activated Neural Networks
by: Leblanc, Benjamin, et al.
Published: (2022)

Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks
by: Haywood-Alexander, Marcus, et al.
Published: (2024)

Admission Control of Quasi-Reversible Queueing Systems: Optimization and Reinforcement Learning
by: Comte, Céline, et al.
Published: (2025)

Uncertainty-Aware Explanations Through Probabilistic Self-Explainable Neural Networks
by: Vadillo, Jon, et al.
Published: (2024)

Physics-Informed Neural PDE Solvers via Spatio-Temporal MeanFlow
by: Bai, Hanru, et al.
Published: (2026)

Concurrent Training and Layer Pruning of Deep Neural Networks
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2024)

Conformalized Physics-Informed Neural Networks
by: Podina, Lena, et al.
Published: (2024)

Physics-Informed Neural Network based Damage Identification for Truss Railroad Bridges
by: Shajihan, Althaf, et al.
Published: (2025)

Explainable Neural Networks with Guarantees: A Sparse Estimation Approach
by: Ledent, Antoine, et al.
Published: (2025)

Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
by: Zheng, Xu, et al.
Published: (2023)

Evaluating Neighbor Explainability for Graph Neural Networks
by: Llorente, Oscar, et al.
Published: (2023)

Explainable Graph Neural Networks Under Fire
by: Li, Zhong, et al.
Published: (2024)

From Text to Graph: Leveraging Graph Neural Networks for Enhanced Explainability in NLP
by: Yáñez-Romero, Fabio, et al.
Published: (2025)

Complexity-Aware Training of Deep Neural Networks for Optimal Structure Discovery
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2024)

Explainable Cross-Disease Reasoning for Cardiovascular Risk Assessment from Low-Dose Computed Tomography
by: Zhang, Yifei, et al.
Published: (2025)

Improved Particle Approximation Error for Mean Field Neural Networks
by: Nitanda, Atsushi
Published: (2024)

Explainable Graph Neural Networks: Understanding Brain Connectivity and Biomarkers in Dementia
by: Tewari, Niharika, et al.
Published: (2025)

Learning Transferable Friction Models and LuGre Identification Via Physics-Informed Neural Networks
by: Ozmen, Asutay, et al.
Published: (2025)

KKT-Informed Neural Network
by: Femine, Carmine Delle
Published: (2024)

Explainable Identification of Hate Speech towards Islam using Graph Neural Networks
by: Wasi, Azmine Toushik
Published: (2023)

Compressing Deep Neural Networks Using Explainable AI
by: Soroush, Kimia, et al.
Published: (2025)

Atherosclerosis through Hierarchical Explainable Neural Network Analysis
by: Adam, Irsyad, et al.
Published: (2025)

Probabilistic Demand Forecasting with Graph Neural Networks
by: Kozodoi, Nikita, et al.
Published: (2024)

Explainable Machine Learning System for Predicting Chronic Kidney Disease in High-Risk Cardiovascular Patients
by: Nguycharoen, Nantika
Published: (2024)

Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics
by: Mousavi-Hosseini, Alireza, et al.
Published: (2024)

Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means
by: Kilian, Valentin, et al.
Published: (2026)

Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators
by: Gan, Weiye, et al.
Published: (2025)

Neurocircuitry-Inspired Hierarchical Graph Causal Attention Networks for Explainable Depression Identification
by: Chen, Weidao, et al.
Published: (2025)