Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model

Objective To develop and validate a deep learning (DL) signature for predicting lymph node (LN) metastasis in patients with lung adenocarcinoma. Methods A total of 612 patients with pathologically-confirmed lung adenocarcinoma were retrospectively enrolled and were randomly divided into training coh...

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Veröffentlicht in:	European radiology 2023-03, Vol.33 (3), p.1949-1962
Hauptverfasser:	Ma, Xiaoling, Xia, Liming, Chen, Jun, Wan, Weijia, Zhou, Wen
Format:	Artikel
Sprache:	eng
Schlagworte:	Adenocarcinoma Adenocarcinoma of Lung - diagnostic imaging Calibration Cancer Computed tomography Decision analysis Deep Learning Diagnostic Radiology Humans Image contrast Image enhancement Imaging Internal Medicine Interventional Radiology Lung cancer Lung Neoplasms - diagnostic imaging Lungs Lymph Nodes Lymphatic Metastasis Lymphatic system Medicine Medicine & Public Health Metastases Metastasis Neuroradiology Oncology Performance evaluation Performance prediction Radiology Radiomics Retrospective Studies Semantics Tomography, X-Ray Computed - methods Transformers Ultrasound
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