A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation A Translational Study to Guide Ablation Therapy
The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to chara...
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| Formaat: | Elektronisch Hoofdstuk |
| Taal: | Engels |
| Gepubliceerd in: |
Karlsruhe
KIT Scientific Publishing
2022
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| Reeks: | Karlsruhe transactions on biomedical engineering
24 |
| Onderwerpen: | |
| Online toegang: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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| 020 | |a 9783731511700 | ||
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| 100 | 1 | |a Patricio Sánchez Arciniegas, Jorge |4 auth | |
| 245 | 1 | 0 | |a A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation |b A Translational Study to Guide Ablation Therapy |
| 260 | |a Karlsruhe |b KIT Scientific Publishing |c 2022 | ||
| 300 | |a 1 electronic resource (162 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Karlsruhe transactions on biomedical engineering |v 24 | |
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate. | ||
| 540 | |a Creative Commons |f by-sa/4.0 |2 cc |4 http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a English | ||
| 650 | 7 | |a Electrical engineering |2 bicssc | |
| 653 | |a Vorhofflimmern | ||
| 653 | |a Fibrose | ||
| 653 | |a maschinelles Lernen | ||
| 653 | |a Bidomain | ||
| 653 | |a Modellierung des Herzens | ||
| 653 | |a atrial fibrillation | ||
| 653 | |a fibrosis | ||
| 653 | |a machine learning | ||
| 653 | |a bidomain | ||
| 653 | |a cardiac modeling | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/bitstream/id/9e9755d6-0af6-4fdb-a898-78cc942afb2d/9783731511700.pdf |7 0 |z OAPEN Library: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/handle/20.500.12657/56965 |7 0 |z OAPEN Library: description of the publication |