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Interleaved Text/Image Deep Mining on a Large-Scale Radiology Database for Automated Image Interpretation.

, , , , , and . J. Mach. Learn. Res., (2016)

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State & Trait Measurement from Nonverbal Vocalizations: A Multi-Task Joint Learning Approach., , , , , , , , , and . INTERSPEECH, page 2028-2032. ISCA, (2022)Anatomy-specific classification of medical images using deep convolutional nets., , , , , , , and . ISBI, page 101-104. IEEE, (2015)Automatic identification of IASLC-defined mediastinal lymph node stations on CT scans using multi-atlas organ segmentation., , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9414 of SPIE Proceedings, page 94141R. SPIE, (2015)Unsupervised Joint Mining of Deep Features and Image Labels for Large-Scale Radiology Image Categorization and Scene Recognition., , , , , , , and . WACV, page 998-1007. IEEE Computer Society, (2017)Large-Scale Nonverbal Vocalization Detection Using Transformers., , , , , , , , , and 3 other author(s). ICASSP, page 1-5. IEEE, (2023)Automated segmentation of thyroid gland on CT images with multi-atlas label fusion and random classification forest., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9414 of SPIE Proceedings, page 941413. SPIE, (2015)Writing Strategies for Science Communication: Data and Computational Analysis., , , and . EMNLP (1), page 5327-5344. Association for Computational Linguistics, (2020)Predicting a multi-parametric probability map of active tumor extent using random forests., , , , , , , , , and 4 other author(s). EMBC, page 6478-6481. IEEE, (2013)Automated segmentation of the thyroid gland on CT using multi-atlas label fusion and random forest., , , , , , , and . ISBI, page 1114-1117. IEEE, (2015)Interleaved text/image Deep Mining on a large-scale radiology database., , , , , and . CVPR, page 1090-1099. IEEE Computer Society, (2015)