Prediction of malignant lymph nodes in NSCLC by machine-learning classifiers using EBUS-TBNA and PET/CT

Prediction of malignant lymph nodes in NSCLC by machine-learning classifiers using EBUS-TBNA and PET/CT

Abstract Accurate determination of lymph-node (LN) metastases is a prerequisite for high precision radiotherapy. The primary aim is to characterise the performance of PET/CT-based machine-learning classifiers to predict LN-involvement by endobronchial ultrasound-guided transbronchial needle aspirati...

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Bibliographic Details
Main Authors: Maja Guberina, Ken Herrmann, Christoph Pöttgen, Nika Guberina, Hubertus Hautzel, Thomas Gauler, Till Ploenes, Lale Umutlu, Axel Wetter, Dirk Theegarten, Clemens Aigner, Wilfried E. E. Eberhardt, Martin Metzenmacher, Marcel Wiesweg, Martin Schuler, Rüdiger Karpf-Wissel, Alina Santiago Garcia, Kaid Darwiche, Martin Stuschke
Format: Article
Language:English
Published: Nature Portfolio 2022-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-21637-y

Internet

https://doi.org/10.1038/s41598-022-21637-y

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