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Learning Invariant Feature Representation to Improve Generalization Across Chest X-Ray Datasets., , , , and . MLMI@MICCAI, volume 12436 of Lecture Notes in Computer Science, page 644-653. Springer, (2020)Behind the scenes: A medical natural language processing project., , , , , , , , , and . I. J. Medical Informatics, (2018)Classification of radiology reports by modality and anatomy: A comparative study., , and . BIBM, page 1457-1464. IEEE Computer Society, (2018)Comparing Rule-Based and Deep Learning Models for Patient Phenotyping., , , , , , , , , and 1 other author(s). CoRR, (2017)Age prediction using a large chest x-ray dataset., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109501U. SPIE, (2019)Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-rays., , , , , , , , , and 2 other author(s). CoRR, (2019)Improving the Path from Diagnoses to Documentation: A Cognitive Review Tool for Clinical Notes and Administrative Records., , , , , and . AMIA, AMIA, (2018)Identifying disease-free chest x-ray images with deep transfer learning., , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109500P. SPIE, (2019)Artificial intelligence for point of care radiograph quality assessment., , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109503K. SPIE, (2019)Automated Detection and Type Classification of Central Venous Catheters in Chest X-Rays., , , , , and . CoRR, (2019)