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- Development of deep learning-based automatic scan range setting model for lung cancer screening low-dose CT imaging.Acad Radiol. 2022; (S1076-6332(21)00566-3. https://doi.org/10.1016/j.acra.2021.12.001)
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- Reduced lung-cancer mortality with volume CT screening in a randomized trial.N Engl J Med. 2020; 382: 503-513
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- A population-based cohort study to evaluate the effectiveness of lung cancer screening using low-dose CT in Hitachi city.Japan. Jpn J Clin Oncol. 2019; 49: 130-136
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- Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.Clin Radiol. 2020; 75: 38-45
- Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms.JAMA Netw Open. 2020; 3e200265
- Artificial intelligence for detection and characterization of pulmonary nodules in lung cancer CT screening: ready for practice?.Transl Lung Cancer Res. 2021; 10: 2378-2388
- Performance and educational training of radiographers in lung nodule or mass detection: retrospective comparison with different deep learning algorithms.Medicine (Baltimore). 2021; 100: e26270
- Comparison of chest radiograph interpretations by artificial intelligence algorithm vs radiology residents.JAMA Netw Open. 2020; 3e2022779
- Lung nodule detectability of artificial intelligence-assisted CT image reading in lung cancer screening.Curr Med Imaging. 2022; 18(3): 327-334
- The relationship between CT scout landmarks and lung boundaries on chest CT: guidelines for minimizing excess z-axis scan length.Eur Radiol. 2020; 30: 581-587
- Automatic scan range delimitation in chest CT using deep learning.Radiol Artif Intell. 2021; 3e200211
Comment on: Ruan J, Meng Y, Zhao F, Gu H, He L, Gong X. Development of Deep Learning-based Automatic Scan Range Setting Model for Lung Cancer Screening Low-dose CT Imaging. Acad Radiol. 2022.