Personalized Cardiac Computer Models and Machine-Learning for Target Vein Selection in Cardiac Resynchronisation Therapy-Reference-Cited by-同舟云学术

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Personalized Cardiac Computer Models and Machine-Learning for Target Vein Selection in Cardiac Resynchronisation Therapy

Published:2023-09-28 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine (CSGB)
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Author:

Bazhutina Anastasia¹,Ushenin Konstantin¹,Khamzin Svyatoslav²,Kabak Vasily¹,Zubarev Stepan³,Lebedev Dmitry³,Solovyova Olga²

Affiliation:

1. Ural Federal University,Ekaterinburg,Russia

2. Institute of Immunology and Physiology UB RAS,Ekaterinburg,Russia

3. Almazov National Medical Research Centre,Saint Petersburg,Russia

Funder

Russian Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10329457/10329623/10329851.pdf?arnumber=10329851

Reference16 articles.

1. Impact of anatomical reverse remodelling in the design of optimal quadripolar pacing leads: A computational study

2. Optimization of Lead Placement in the Right Ventricle During Cardiac Resynchronization Therapy. A Simulation Study

3. Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart

4. Machine Learning Prediction of Cardiac Resynchronisation Therapy Response From Combination of Clinical and Model-Driven Data

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

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