Deep learning-based prediction of nodal metastasis in lung cancer using endobronchial ultrasoundCentral MessagePerspective

Deep learning-based prediction of nodal metastasis in lung cancer using endobronchial ultrasoundCentral MessagePerspective

Objective: Endobronchial ultrasound-guided transbronchial needle aspiration is a vital tool for mediastinal and hilar lymph node staging in patients with lung cancer. Despite its high diagnostic performance and safety, it has a limited negative predictive value. Our objective was to evaluate the dia...

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Bibliographic Details
Main Authors: Tsukasa Ishiwata, MD, PhD, Terunaga Inage, MD, PhD, Masato Aragaki, MD, PhD, Alexander Gregor, MD, PhD, Zhenchian Chen, MD, Nicholas Bernards, PhD, Kamran Kafi, MD, Kazuhiro Yasufuku, MD, PhD
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:JTCVS Techniques
Subjects:
endobronchial ultrasound
artificial intelligence
deep learning
convolutional neural networks
diagnostic accuracy
Online Access:http://www.sciencedirect.com/science/article/pii/S2666250724003705
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