Real-Time Radiofrequency Ablation Lesion Depth Estimation Using Multi-frequency Impedance With a Deep Neural Network and Tree-Based Ensembles-Reference-Cited by-同舟云学术

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Real-Time Radiofrequency Ablation Lesion Depth Estimation Using Multi-frequency Impedance With a Deep Neural Network and Tree-Based Ensembles

Published:2020-07 Issue:7 Volume:67 Page:1890-1899
ISSN:0018-9294
Container-title:IEEE Transactions on Biomedical Engineering
language:
Short-container-title:IEEE Trans. Biomed. Eng.

Author:

Besler Emre^ORCID,Wang Yearnchee Curtis,Sahakian Alan V.^ORCID

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Link

https://ieeexplore.ieee.org/ielam/10/9119878/8886409-aam.pdf

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MRI Accurately Visualizes RF Ablation Delivery Targeted to MRI-Defined Arrhythmia Substrates in the Left Ventricle;IEEE Transactions on Biomedical Engineering;2024-09

2. Predicting spatio-temporal radiofrequency ablation temperature using deep neural networks;Medical Engineering & Physics;2024-02

3. Machine learning model for preoperative assessment of ultrasound diathermy with implants;International Journal of Thermal Sciences;2023-11

4. Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses;APL Machine Learning;2023-08-16

5. Multilayer spintronic neural networks with radiofrequency connections;Nature Nanotechnology;2023-07-27

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