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Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy

Abstract New bronchoscopy techniques like radial probe endobronchial ultrasound have been developed for real-time sampling characterization, but their use is still limited. This study aims to use classification algorithms with minimally invasive electrical impedance spectroscopy to improve neoplasti...

Celý popis

Uloženo v:
Hlavní autoři: Georgina Company-Se, Virginia Pajares, Albert Rafecas-Codern, Pere J. Riu, Javier Rosell-Ferrer, Ramon Bragós, Lexa Nescolarde
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Portfolio 2025-03-01
Edice:Scientific Reports
Témata:
Classification
Machine learning
Minimally-invasive bioimpedance
Bronchoscopy
Neoplasm
On-line přístup:https://doi.org/10.1038/s41598-025-94826-0
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