This paper is in the following e-collection/theme issue:

Artificial Intelligence (122) Artificial Intelligence (1216) Clinical Informatics (919) Clinical Information and Decision Making (1340) Machine Learning (1401)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44537, first published .
Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning–Based Natural Language Processing

Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning–Based Natural Language Processing

Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning–Based Natural Language Processing

Authors of this article:

Kyeryoung Lee1 Author Orcid Image ;   Zongzhi Liu1 Author Orcid Image ;   Urmila Chandran2 Author Orcid Image ;   Iftekhar Kalsekar2 Author Orcid Image ;   Balaji Laxmanan2 Author Orcid Image ;   Mitchell K Higashi1 Author Orcid Image ;   Tomi Jun1 Author Orcid Image ;   Meng Ma1 Author Orcid Image ;   Minghao Li1 Author Orcid Image ;   Yun Mai1 Author Orcid Image ;   Christopher Gilman1 Author Orcid Image ;   Tongyu Wang1 Author Orcid Image ;   Lei Ai1 Author Orcid Image ;   Parag Aggarwal1 Author Orcid Image ;   Qi Pan1 Author Orcid Image ;   William Oh3 Author Orcid Image ;   Gustavo Stolovitzky1 Author Orcid Image ;   Eric Schadt3 Author Orcid Image ;   Xiaoyan Wang1 Author Orcid Image
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