Combination of personalized computational modeling and machine learning for optimization of left ventricular pacing site in cardiac resynchronization therapy

A Dokuchaev, T Chumarnaya, A Bazhutina… - Frontiers in …, 2023 - frontiersin.org
Introduction: The 30–50% non-response rate to cardiac resynchronization therapy (CRT)
calls for improved patient selection and optimized pacing lead placement. The study aimed …

Applied Sciences—Special Issue on Emerging Techniques in Imaging, Modelling and Visualization for Cardiovascular Diagnosis and Therapy

CA Linte, M Pop - Applied Sciences, 2023 - mdpi.com
Ongoing developments in computing and data acquisition, along with continuous advances
in medical imaging technology, computational modelling, robotics and visualization have …

[引用][C] Arsenii Dokuchaev1, Tatiana Chumarnaya1, 2, Anastasia Bazhutina1, 2, Svyatoslav Khamzin1, Viktoria Lebedeva3, Tamara Lyubimtseva1, 3, Stepan Zubarev1 …

A Dokuchaev, T Chumarnaya, A Bazhutina, S Khamzin… - 2023 - europepmc.org
Materials and methods: We reviewed retrospective data for 57 CRT recipients. A positive
response was defined as a more than 10% LVEF improvement. Personalized models of …