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Automated radiology report generation has the potential to improve radiology reporting and alleviate the workload of radiologists.
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Shin, H.C., Roberts, K., Lu, L., Demner-Fushman, D., Yao, J., Summers, R.M.: Learning to read chest x-rays: Recurrent neural cascade model for automated image annotation. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 2497–2506 (2016)
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Jing, B., Xie, P., Xing, E.P.: On the automatic generation of medical imaging reports. In: Annual Meeting of the Association for Computational Linguistics (2017)
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Li, P., Zhang, H., Liu, X., Shi, S.: Rigid formats controlled text generation. In: ACL. pp. 742–751 (2020)
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Srinivasan, P., Thapar, D., Bhavsar, A., Nigam, A.: Hierarchical x-ray report generation via pathology tags and multi head attention. In: Ishikawa, H., Liu, C.L., Pajdla, T., Shi, J. (eds.) Computer Vision – ACCV 2020. pp. 600–616. Springer International Publishing, Cham (2021)
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Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I.: Attention is all you need. Advances in neural information processing systems 30
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Xue, Y., Xu, T., Long, L.R., Xue, Z., Antani, S.K., Thoma, G.R., Huang, X.: Multimodal recurrent model with attention for automated radiology report generation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention (2018)
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Irvin, J.A., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R.L., Shpanskaya, K.S., Seekins, J., Mong, D.A., Halabi, S.S., Sandberg, J.K., Jones, R., Larson, D.B., Langlotz, C., Patel, B.N., Lungren, M.P., Ng, A.: Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison. In: AAAI Conference on Artificial Intelligence (2019)
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Liu, F., Ge, S., Wu, X.: Competence-based multimodal curriculum learning for medical report generation. In: Annual Meeting of the Association for Computational Linguistics (2022)
2022
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Chen, Y.J., Shen, W.H., Chung, H.W., Chiu, C.H., Juan, D.C., Ho, T.Y., Cheng, C.T., Li, M.L., Ho, T.Y.: Representative image feature extraction via contrastive learning pretraining for chest x-ray report generation (2023)
2023
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2023
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Ma, J., Wang, B.: Segment anything in medical images. arXiv preprint arXiv:2304.12306 (2023)
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Yin, C., Li, P., Ren, Z.: Ctrlstruct: Dialogue structure learning for open-domain response generation. In: Proceedings of the ACM Web Conference 2023. p. 1539–1550. WWW ’23, Association for Computing Machinery, New York, NY, USA (2023). https://doi.org/10.1145/3543507.3583285, https://doi.org/10.1145/3543507.3583285
2023
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