Cargando…
Does a Deep Learning–Based Computer-Assisted Diagnosis System Outperform Conventional Double Reading by Radiologists in Distinguishing Benign and Malignant Lung Nodules?
BACKGROUND: In differentiating indeterminate pulmonary nodules, multiple studies indicated the superiority of deep learning–based computer-assisted diagnosis system (DL-CADx) over conventional double reading by radiologists, which needs external validation. Therefore, our aim was to externally valid...
Autores principales: | Liu, Zhou, Li, Li, Li, Tianran, Luo, Douqiang, Wang, Xiaoliang, Luo, Dehong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7581733/ https://www.ncbi.nlm.nih.gov/pubmed/33163395 http://dx.doi.org/10.3389/fonc.2020.545862 |
Ejemplares similares
-
Evaluating the performance of a deep learning‐based computer‐aided diagnosis (DL‐CAD) system for detecting and characterizing lung nodules: Comparison with the performance of double reading by radiologists
por: Li, Li, et al.
Publicado: (2018) -
Elastography in Distinguishing Benign from Malignant Thyroid Nodules
por: Colakoglu, Bulent, et al.
Publicado: (2016) -
Liquid biopsies to distinguish malignant from benign pulmonary nodules
por: Tao, Rui, et al.
Publicado: (2021) -
Improvement of diagnostic efficiency in distinguishing the benign and malignant thyroid nodules via conventional ultrasound combined with ultrasound contrast and elastography
por: Liu, Mei-Juan, et al.
Publicado: (2017) -
Diffusion Kurtosis MR Imaging versus Conventional Diffusion-Weighted Imaging for Distinguishing Hepatocellular Carcinoma from Benign Hepatic Nodules
por: Jia, Yingmei, et al.
Publicado: (2019)