Progressive Transformer-Based Generation of Radiology Reports
Farhad Nooralahzadeh | Nicolas Perez Gonzalez | Thomas Frauenfelder | Koji Fujimoto | Michael Krauthammer
Findings of the Association for Computational Linguistics: EMNLP 2021
Inspired by Curriculum Learning, we propose a consecutive (i.e., image-to-text-to-text) generation framework where we divide the problem of radiology report generation into two steps. Contrary to generating the full radiology report from the image at once, the model generates global concepts from the image in the first step and then reforms them into finer and coherent texts using transformer-based architecture. We follow the transformer-based sequence-to-sequence paradigm at each step. We improve upon the state-of-the-art on two benchmark datasets.
The Transliteration from Alphabet Queries to Japanese Product Names
Rieko Tsuji | Yoshinori Nemoto | Wimvipa Luangpiensamut | Yuji Abe | Takeshi Kimura | Kanako Komiya | Koji Fujimoto | Yoshiyuki Kotani
Proceedings of the 26th Pacific Asia Conference on Language, Information, and Computation
Negation Naive Bayes for Categorization of Product Pages on the Web
Kanako Komiya | Naoto Sato | Koji Fujimoto | Yoshiyuki Kotani
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011
- Kanako Komiya 2
- Yoshiyuki Kotani 2
- Naoto Sato 1
- Rieko Tsuji 1
- Yoshinori Nemoto 1
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