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Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge., , , , , , , , , and 21 other author(s). CoRR, (2016)Structure and position-aware graph neural network for airway labeling., , , and . CoRR, (2022)Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images., , , , , , and . IEEE Trans. Medical Imaging, 34 (4): 962-973 (2015)Nodule detection and generation on chest X-rays: NODE21 Challenge., , , , , , , , , and 9 other author(s). CoRR, (2024)Computer-aided detection of lung cancer: combining pulmonary nodule detection systems with a tumor risk prediction model., , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9414 of SPIE Proceedings, page 94141O. SPIE, (2015)Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study., , , , , , , and . CoRR, (2020)Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks., , , , , , , , , and . IEEE Trans. Medical Imaging, 35 (5): 1160-1169 (2016)Exploring the interpretability of deep neural networks used for gravitational lens finding with a sensitivity probe., , , and . Astron. Comput., (2022)Kidney abnormality segmentation in thorax-abdomen CT scans., , , , , and . CoRR, (2023)Automated COVID-19 Grading With Convolutional Neural Networks in Computed Tomography Scans: A Systematic Comparison., , , , , , , and . IEEE Trans. Artif. Intell., 3 (2): 129-138 (2022)