Cargando…
Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules
Rationale: The management of indeterminate pulmonary nodules (IPNs) remains challenging, resulting in invasive procedures and delays in diagnosis and treatment. Strategies to decrease the rate of unnecessary invasive procedures and optimize surveillance regimens are needed. Objectives: To develop an...
Autores principales: | Massion, Pierre P., Antic, Sanja, Ather, Sarim, Arteta, Carlos, Brabec, Jan, Chen, Heidi, Declerck, Jerome, Dufek, David, Hickes, William, Kadir, Timor, Kunst, Jonas, Landman, Bennett A., Munden, Reginald F., Novotny, Petr, Peschl, Heiko, Pickup, Lyndsey C., Santos, Catarina, Smith, Gary T., Talwar, Ambika, Gleeson, Fergus |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Thoracic Society
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365375/ https://www.ncbi.nlm.nih.gov/pubmed/32326730 http://dx.doi.org/10.1164/rccm.201903-0505OC |
Ejemplares similares
-
Development and validation of clinical prediction models to risk stratify patients presenting with small pulmonary nodules: a research protocol
por: Oke, Jason L., et al.
Publicado: (2018) -
External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules
por: Baldwin, David R, et al.
Publicado: (2020) -
(18)F-FSPG PET imaging for the evaluation of indeterminate pulmonary nodules
por: Paez, Rafael, et al.
Publicado: (2022) -
Dual-energy CT in the diagnosis of occult acute scaphoid injury: a direct comparison with MRI
por: Xie, Cheng, et al.
Publicado: (2020) -
Evaluation of a novel deep learning–based classifier for perifissural nodules
por: Han, Daiwei, et al.
Publicado: (2020)