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

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 to develop a novel technique using patient-specific cardiac models and machine learning (ML) to predict an optimal left vent...

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Detalles Bibliográficos
Autores principales: Dokuchaev, Arsenii, Chumarnaya, Tatiana, Bazhutina, Anastasia, Khamzin, Svyatoslav, Lebedeva, Viktoria, Lyubimtseva, Tamara, Zubarev, Stepan, Lebedev, Dmitry, Solovyova, Olga
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10367108/
https://www.ncbi.nlm.nih.gov/pubmed/37497440
http://dx.doi.org/10.3389/fphys.2023.1162520

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10367108/
https://www.ncbi.nlm.nih.gov/pubmed/37497440
http://dx.doi.org/10.3389/fphys.2023.1162520

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