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Detail-on-Demand Visualization for Lean Understanding of Lung Abnormalities.

, , , , , and . MMVR, volume 173 of Studies in Health Technology and Informatics, page 362-368. IOS Press, (2012)

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Active Relearning for Robust Supervised Training of Emphysema Patterns., , , , and . J. Digital Imaging, 27 (4): 548-555 (2014)A deep neural network predicts survival after heart imaging better than cardiologists., , , , , , , , , and 5 other author(s). CoRR, (2018)Quantitative image analytics for stratified pulmonary medicine., , , , and . ISBI, page 1779-1782. IEEE, (2012)Active relearning for robust supervised classification of pulmonary emphysema., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 8315 of SPIE Proceedings, page 83152Q. SPIE, (2012)Automating the expert consensus paradigm for robust lung tissue classification., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 8315 of SPIE Proceedings, page 831530. SPIE, (2012)Referenceless Stratification of Parenchymal Lung Abnormalities., , , , and . MICCAI (3), volume 6893 of Lecture Notes in Computer Science, page 223-230. Springer, (2011)Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data., , , , , , , , , and 5 other author(s). CoRR, (2019)Detail-on-Demand Visualization for Lean Understanding of Lung Abnormalities., , , , , and . MMVR, volume 173 of Studies in Health Technology and Informatics, page 362-368. IOS Press, (2012)Quantitative consensus of supervised learners for diffuse lung parenchymal HRCT patterns., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 8670 of SPIE Proceedings, page 867037. SPIE, (2013)Effect of denoising on supervised lung parenchymal clusters., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 8315 of SPIE Proceedings, page 83152X. SPIE, (2012)