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A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19)

This study was approved by the Ethics of Committees of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (No. 2020-0026), and followed the 1964 Helsinki Declaration ...

Nature

Better performance of deep learning pulmonary nodule detection using chest radiography with pixel level labels in reference to computed tomography: data quality matters

Labeling errors can significantly impact the performance of deep learning models used for screening chest radiographs. The deep learning model for detecting pulmonary nodules is particularly ...

ascopubs.org

Deep learning–based chest CT model to predict treatment response to immune checkpoint inhibitors in non-small cell lung cancer independently and additively to ...

Immune infiltrate characterization and differential gene expression by RNA-sequencing analysis in patients with oncogene-addicted NSCLC with early progression under targeted therapy. This is an ASCO ...

ascopubs.org

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A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19)

Better performance of deep learning pulmonary nodule detection using chest radiography with pixel level labels in reference to computed tomography: data quality matters

Deep learning–based chest CT model to predict treatment response to immune checkpoint inhibitors in non-small cell lung cancer independently and additively to ...

Deep learning signature from chest CT and association with immunotherapy outcomes in EGFR/ALK-negative NSCLC.

Deep learning for reticular opacity on chest radiographs with interstitial lung disease

Open-source algorithm predicts heart attack risk from chest CT scan

Deep learning for reticular opacity on chest radiographs with interstitial lung disease