Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning–Based Natural Language Processing
BackgroundGround-glass opacities (GGOs) appearing in computed tomography (CT) scans may indicate potential lung malignancy. Proper management of GGOs based on their features can prevent the development of lung cancer. Electronic health records are rich sources of information...
Main Authors: | Kyeryoung Lee, Zongzhi Liu, Urmila Chandran, Iftekhar Kalsekar, Balaji Laxmanan, Mitchell K Higashi, Tomi Jun, Meng Ma, Minghao Li, Yun Mai, Christopher Gilman, Tongyu Wang, Lei Ai, Parag Aggarwal, Qi Pan, William Oh, Gustavo Stolovitzky, Eric Schadt, Xiaoyan Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
JMIR Publications
2023-06-01
|
Series: | JMIR AI |
Online Access: | https://ai.jmir.org/2023/1/e44537 |
Similar Items
-
Diagnostic outcomes of robotic-assisted bronchoscopy for pulmonary lesions in a real-world multicenter community setting
by: Faisal Khan, et al.
Published: (2023-05-01) -
Peripheral consolidation/ground-glass opacities
by: Edson Marchiori, et al.
Published: (2020-01-01) -
The metaphysics of opacity
by: Diehl, C, et al.
Published: (2023) -
Photoionization and Opacity
by: Anil Pradhan
Published: (2023-03-01) -
911 Improved lifelines needed for all lines: real-world treatment patterns and attrition rates in US patients with non-driver mutation metastatic non-small cell lung cancer
by: Chen Hu, et al.
Published: (2023-11-01)