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...

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Detalhes bibliográficos

Principais autores:	Georgina Company-Se, Virginia Pajares, Albert Rafecas-Codern, Pere J. Riu, Javier Rosell-Ferrer, Ramon Bragós, Lexa Nescolarde
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-03-01
coleção:	Scientific Reports
Assuntos:	Classification Machine learning Minimally-invasive bioimpedance Bronchoscopy Neoplasm
Acesso em linha:	https://doi.org/10.1038/s41598-025-94826-0
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