Atrial constitutive neural networks
This work addresses the need for improved simulation and prediction of cardiac health, representing an incremental step in modeling atrial mechanics.
The authors tackled the problem of characterizing atrial tissue mechanics by using constitutive neural networks to automatically discover appropriate material models from experimental data, overcoming limitations of traditional predefined models.
This work presents a novel approach for characterizing the mechanical behavior of atrial tissue using constitutive neural networks. Based on experimental biaxial tensile test data of healthy human atria, we automatically discover the most appropriate constitutive material model, thereby overcoming the limitations of traditional, pre-defined models. This approach offers a new perspective on modeling atrial mechanics and is a significant step towards improved simulation and prediction of cardiac health.