April 1, 2025
The purpose of our study is to describe the feasibility of a computational fluid dynamics model to predict hepatic artery flow and its variations following gastroduodenal (GDA) or common hepatic
February 18, 2025
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE JOURNAL. The objective of this study is to present framework, validated both against literature and experiments, aiming to enable intervertebral disc
February 10, 2025
Vall d'Hebron hosts a Cafè GIPS event, where doctors, engineers and scientists share how interdisciplinary collaboration transforms diagnoses and treatments, from 3D technology to digital
December 26, 2024
Our results show significant differences between 3D and 0D single-cell models as risk levels increase, underscoring the ability of 3D modeling to capture more complex cardiac
December 25, 2024
The objectives of our work are to create computational models of electrophysiology of human cardiac anatomies with a range of detail, reproduce a LBBB population of patients with and without CRT
December 18, 2024
Virtual humans and digital twins for testing drugs and
October 28, 2024
This study presents a proof-of-principle pipeline to build personalized digital cardiac twins by integrating cardiovascular MRI and electrocardiographic
July 5, 2024
The EU-funded research consortium on virtual human twins for a more effective and personalized treatment of complex cardiovascular
May 30, 2024
By simulating human organs, companies like ELEM Biotech can predict how patients will respond to various treatments, thus enhancing safety and
April 29, 2024
In this study, we present a systematic evaluation of CRT pacing protocols through an in silico clinical trial based on a patient-specific digital twin cohort of Left Bundle Branch Block (LBBB)
April 18, 2024
JOURNAL OF PHARMACOLOGICAL AND TOXICOLOGICAL METHODS. While current computational methodologies focus on predicting the incidence of proarrhythmic events after drug administration, the objective of
April 18, 2024
This study represents a significant step towardsintegrating in silico technologies into real clinical contexts, providing a robust framework for improving aortic stenosis diagnosis and the design of