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Automatic Bounding Box Annotation of Chest X-Ray Data for Localization of Abnormalities., , , , , , and . ISBI, page 799-803. IEEE, (2020)Boosting the Rule-Out Accuracy of Deep Disease Detection Using Class Weight Modifiers., , , , and . ISBI, page 877-881. IEEE, (2019)Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-Rays., , , , , , , , , and 2 other author(s). ISBI, page 863-867. IEEE, (2019)Visual Dialog for Radiology: Data Curation and FirstSteps., , , , , , , , , and 2 other author(s). ViGIL@NeurIPS, (2019)Visual Localization of Wireless Capsule Endoscopes Aided by Artificial Neural Networks., , , , and . CBMS, page 734-738. IEEE Computer Society, (2017)Chest x-ray generation and data augmentation for cardiovascular abnormality classification., , , and . Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 105741M. SPIE, (2018)Semi-supervised learning with generative adversarial networks for chest X-ray classification with ability of data domain adaptation., , , and . ISBI, page 1038-1042. IEEE, (2018)Universal multi-modal deep network for classification and segmentation of medical images., , , , and . ISBI, page 872-876. IEEE, (2018)Quality controlled segmentation to aid disease detection., , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Artificial intelligence for point of care radiograph quality assessment., , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109503K. SPIE, (2019)