High-Frequency Irreversible Electroporation: Optimum Parameter Prediction via Machine-Learning-Reference-Cited by-同舟云学术

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High-Frequency Irreversible Electroporation: Optimum Parameter Prediction via Machine-Learning

Published:2024-09 Issue:3 Volume:8 Page:220-228
ISSN:2469-7249
Container-title:IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology
language:
Short-container-title:IEEE J. Electromagn. RF Microw. Med. Biol.

Author:

De Cillis A.¹^ORCID,Merla C.²^ORCID,Monti G.¹^ORCID,Tarricone L.¹^ORCID,Zappatore M.¹^ORCID

Affiliation:

1. Engineering for Innovation Department, University of Salento, Lecce, Italy

2. Division of Health Protection Technologies, ENEA, Rome, Italy

Funder

ECS

European Union- Next GenerationEU

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7397573/10643568/10486922.pdf?arnumber=10486922

Reference27 articles.

1. Machine Learning for H-FIRE Protocols: Tuning Parameters for High-Frequency Irreversible Electroporation by Machine Learning

2. Tumor location on electroporation therapies by means of multi-electrode structures and machine learning

3. High-Voltage Electrical Pulses in Oncology: Irreversible Electroporation, Electrochemotherapy, Gene Electrotransfer, Electrofusion, and Electroimmunotherapy

4. Impact of needle positioning on ablation success of irreversible electroporation: a unicentric retrospective analysis

5. Nano-pulse stimulation induces potent immune responses, eradicating local breast cancer while reducing distant metastases

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