Next-generation tissue-engineered heart valves with repair, remodelling and regeneration capacity
ES Fioretta, SE Motta, V Lintas, S Loerakker… - Nature Reviews …, 2021 - nature.com
Valvular heart disease is a major cause of morbidity and mortality worldwide. Surgical valve
repair or replacement has been the standard of care for patients with valvular heart disease …
repair or replacement has been the standard of care for patients with valvular heart disease …
Scaling digital twins from the artisanal to the industrial
Mathematical modeling and simulation are moving from being powerful development and
analysis tools towards having increased roles in operational monitoring, control and …
analysis tools towards having increased roles in operational monitoring, control and …
The openCARP simulation environment for cardiac electrophysiology
Abstract Background and Objective: Cardiac electrophysiology is a medical specialty with a
long and rich tradition of computational modeling. Nevertheless, no community standard for …
long and rich tradition of computational modeling. Nevertheless, no community standard for …
Artificial intelligence and machine learning in arrhythmias and cardiac electrophysiology
Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of
intense exploration, showing potential to automate human tasks and even perform tasks …
intense exploration, showing potential to automate human tasks and even perform tasks …
Machine learning in arrhythmia and electrophysiology
Machine learning (ML), a branch of artificial intelligence, where machines learn from big
data, is at the crest of a technological wave of change sweeping society. Cardiovascular …
data, is at the crest of a technological wave of change sweeping society. Cardiovascular …
Artificial intelligence in the diagnosis and management of arrhythmias
VD Nagarajan, SL Lee, JL Robertus… - European heart …, 2021 - academic.oup.com
The field of cardiac electrophysiology (EP) had adopted simple artificial intelligence (AI)
methodologies for decades. Recent renewed interest in deep learning techniques has …
methodologies for decades. Recent renewed interest in deep learning techniques has …
Predicting atrial fibrillation recurrence by combining population data and virtual cohorts of patient-specific left atrial models
Background: Current ablation therapy for atrial fibrillation is suboptimal, and long-term
response is challenging to predict. Clinical trials identify bedside properties that provide only …
response is challenging to predict. Clinical trials identify bedside properties that provide only …
Computational models of atrial fibrillation: Achievements, challenges, and perspectives for improving clinical care
Despite significant advances in its detection, understanding and management, atrial
fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on …
fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on …
Critical appraisal of technologies to assess electrical activity during atrial fibrillation: A position paper from the European heart rhythm association and European …
We aim to provide a critical appraisal of basic concepts underlying signal recording and
processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF …
processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF …
The physics of heart rhythm disorders
WJ Rappel - Physics reports, 2022 - Elsevier
The global burden caused by cardiovascular disease is substantial, with heart disease
representing the most common cause of death around the world. There remains a need to …
representing the most common cause of death around the world. There remains a need to …