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

Kyeryoung Lee   1 * , PhD ;   Zongzhi Liu   1 * , PhD ;   Urmila Chandran   2 , PhD ;   Iftekhar Kalsekar   2 , PhD ;   Balaji Laxmanan   2 , MD ;   Mitchell K Higashi   1 , PhD ;   Tomi Jun   1 , MD ;   Meng Ma   1 , PhD ;   Minghao Li   1 , MSc ;   Yun Mai   1 , PhD ;   Christopher Gilman   1 , BSc ;   Tongyu Wang   1 , BSc ;   Lei Ai   1 , PhD ;   Parag Aggarwal   1 , PhD ;   Qi Pan   1 , PhD ;   William Oh   3 , MD ;   Gustavo Stolovitzky   1 , PhD ;   Eric Schadt   3 , PhD ;   Xiaoyan Wang   1 , PhD

1 Sema4, Stamford, CT, United States

2 Lung Cancer Initiative, Johnson & Johnson, New Brunswick, NJ, United States

3 Icahn School of Medicine at Mount Sinai, New York, NY, United States

*these authors contributed equally

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