DeepCUBIT: Predicting Lymphovascular Invasion or Pathological Lymph Node Involvement of Clinical T1 Stage Non-Small Cell Lung Cancer on Chest CT Scan Using Deep Cubical Nodule Transfer Learning Algorithm

DeepCUBIT: Predicting Lymphovascular Invasion or Pathological Lymph Node Involvement of Clinical T1 Stage Non-Small Cell Lung Cancer on Chest CT Scan Using Deep Cubical Nodule Transfer Learning Algorithm

The prediction of lymphovascular invasion (LVI) or pathological nodal involvement of tumor cells is critical for successful treatment in early stage non-small cell lung cancer (NSCLC). We developed and validated a Deep Cubical Nodule Transfer Learning Algorithm (DeepCUBIT) using transfer learning an...

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Bibliographic Details
Main Authors: Kyongmin Sarah Beck, Bomi Gil, Sae Jung Na, Ji Hyung Hong, Sang Hoon Chun, Ho Jung An, Jae Jun Kim, Soon Auck Hong, Bora Lee, Won Sang Shim, Sungsoo Park, Yoon Ho Ko
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Oncology
Subjects:
deep learning
non-small cell lung cancer
prognosis
computed tomography
lobectomy
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2021.661244/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2021.661244/full

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