Deep learning for predicting subtype classification and survival of lung adenocarcinoma on computed tomography
Objectives: The subtype classification of lung adenocarcinoma is important for treatment decision. This study aimed to investigate the deep learning and radiomics networks for predicting histologic subtype classification and survival of lung adenocarcinoma diagnosed through computed tomography (CT)...
Main Authors: | Chengdi Wang, Jun Shao, Junwei Lv, Yidi Cao, Chaonan Zhu, Jingwei Li, Wei Shen, Lei Shi, Dan Liu, Weimin Li |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2021-08-01
|
Series: | Translational Oncology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1936523321001339 |
Similar Items
-
Novel immune subtypes of lung adenocarcinoma identified through bioinformatic analysis
by: Fang‐lu Qin, et al.
Published: (2020-09-01) -
Identification of Distinct Molecular Subtypes of Endometrioid Adenocarcinoma
by: Jia Lei, et al.
Published: (2021-07-01) -
Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma
by: Hao Sun, et al.
Published: (2020-10-01) -
Analysis of clinicopathology and CT features of histology subtypes of invasive lung adenocarcinoma
by: HE Xiaoqun, et al.
Published: (2020-10-01) -
Correlation Study of 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Pathological Subtypes of Invasive Lung Adenocarcinoma and Prognosis
by: Bin Yang, et al.
Published: (2019-09-01)