The current research lines in Physense include:
- Patient-specific computational fluid simulations for medical decisions related to the implantation of left atrial appendage occluder devices and the risk of thrombus in atrial fibrillation patients (VIROLAAI Retos I+D national project, SimCardioTest Horizon2020 EU project; Andy L. Olivares, Jordi Mill, Carlos Albors, Marta Sáiz)
- Advanced visual analytics interfaces and computer graphics algorithms (e.g., augmented/virtual reality headsets, web-based platforms and cinematic rendering) for an improved and interactive medical data visualisation (Irem Baseer, Jasna Nuhic, Ainhoa Aguado, Àngel Herrero, Pablo Acedo);
- Biomechanical models of brain development to better understand cortical abnormalities during pregnancy (ERA-Net Neuron project; Mireia Alenyà)
- Deep learning-based analysis of complex imaging data such as 4D flow magnetic resonance or echocardiographic imaging as well as different types of electrophysiological signal (e.g., electrocardiograms, electrograms, Holter) data (Guillermo Jiménez-Pérez, Xabier Morales, Irem Cetin).
- Development of explainable artificial intelligence algorithms (e.g., variational autoencoders, multiple kernel learning) to identify the most relevant and interpretable biomarkers for clinical decisions from large multimodal datasets
- Electrophysiological simulations of the heart to support ablation-based therapies in arrhythmic (e.g., atrial fibrillation, ventricular tachycardia) patients (Álvaro Bocanegra).