Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening

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Convolutional neural networks: an overview and application in radiology (2018, background): “For example, low-dose CT was shown to be useful for lung cancer screening [51].”
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge (2016, methodology): “We only considered annotations categorized as nodules ≥ 3 mm as relevant lesions, as nodules < 3 mm, and non-nodule lesions are not considered relevant for lung cancer screening protocols (Aberle et al. (2011)).”
Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks (2017, methodology): “Moreover, Aidence trained its model using the labeled data on the NLST dataset [1], therefore, its result is actually incomparable to ours.”
Cancer statistics, 2016 (2016, background): “There is promise for improving lung cancer survival rates because of earlier detection through screening with spiral computed tomography.(46) However, it is important to realize that screening, as well as other changes in detection practices, introduces lead time bias in survival rates, thereby redu”